From 125b7e056d921ff23ec8975278edaa8ef3679289 Mon Sep 17 00:00:00 2001
From: ksun <sunkai71@huawei.com>
Date: Tue, 3 Sep 2024 09:30:18 +0000
Subject: [PATCH 1/4] =?UTF-8?q?mysql=20=E7=BA=BF=E7=A8=8B=E6=B1=A0?=
 =?UTF-8?q?=E9=87=87=E9=9B=86=E6=9B=B4=E6=96=B0?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: ksun <sunkai71@huawei.com>
---
 tools/collect_msg.sh | 38 +++++++++++++++++++++++++++++++-------
 1 file changed, 31 insertions(+), 7 deletions(-)

diff --git a/tools/collect_msg.sh b/tools/collect_msg.sh
index c872fb7..113d2d8 100644
--- a/tools/collect_msg.sh
+++ b/tools/collect_msg.sh
@@ -183,9 +183,10 @@ collect_database(){
        echo "Process mysql started."
        # 执行下一步操作
        sleep 5
-       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "select * from INFORMATION_SCHEMA.plugins where PLUGIN_NAME like 'thread_pool%'" > $log_path/database_mysql.log
+       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "select * from INFORMATION_SCHEMA.plugins where PLUGIN_NAME like 'thread_pool%'" > $log_path/database_mysql_thread_pool.log
+       echo thread_pool: $(ls $plugin_path |grep thread_pool.so) >> $log_path/database_mysql_thread_pool.log
+       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "show variables like 'thread_pool%'" > $log_path/database_mysql_thread_pool_variable.log
        $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "select * from INFORMATION_SCHEMA.plugins where PLUGIN_NAME like 'kovae%'" >> $log_path/database_mysql.log
-       echo thread_pool: $(ls $plugin_path |grep thread_pool.so) >> $log_path/database_mysql.log
        echo kovae_path: $(ls $plugin_path |grep ha_kovae.so) >>  $log_path/database_mysql.log
        readelf -a $mysql_install_path/bin/mysqld|grep bolt >> $log_path/database_mysql.log
        echo no_lock: $(objdump -d $mysql_install_path/bin/mysqld|grep -c row_vers_build_for_semi_consistent_readP5trx_t) >> $log_path/database_mysql.log
@@ -274,7 +275,8 @@ collect_ccos_msg(){
     /vendor/bin/tee-check > $log_path/virtccos_itrustee.log
     tlogcat -f &
     sleep 3s
-    cat /var/log/tee/teeOS_log-0  | grep TA_UUID >> $log_path/virtccos_itrustee.log
+    cat /var/log/tee/teeOS_log-0  | grep UUID >> $log_path/virtccos_itrustee.log
+    ps aux | grep tlogcat | awk '{print $2}' | xargs kill
 }
 
 
@@ -662,7 +664,7 @@ EOF
   --conf spark.executor.extraLibraryPath=$omnidata_install_path/haf-host/lib \
   --conf spark.executorEnv.HAF_CONFIG_PATH=$omnidata_install_path/haf-host/etc/ \
   --name tpcds_test.sql --driver-memory 50G --driver-java-options -Dlog4j.configuration=file:/tmp/log4j.properties \
-  --executor-memory 32G --num-executors 30 --executor-cores 18 --database tpcds_bin_partitioned_varchar_orc_2 \
+  --executor-memory 32G --num-executors 30 --executor-cores 18 --database $database \
   -e "WITH customer_total_return AS ( SELECT sr_customer_sk AS ctr_customer_sk, sr_store_sk AS ctr_store_sk, sum(sr_return_amt) AS ctr_total_return FROM store_returns, date_dim WHERE sr_returned_date_sk = d_date_sk AND d_year = 2000 GROUP BY sr_customer_sk, sr_store_sk) SELECT c_customer_id FROM customer_total_return ctr1, store, customer WHERE ctr1.ctr_total_return > (SELECT avg(ctr_total_return) * 1.2 FROM customer_total_return ctr2 WHERE ctr1.ctr_store_sk = ctr2.ctr_store_sk) AND s_store_sk = ctr1.ctr_store_sk AND s_state = 'TN' AND ctr1.ctr_customer_sk = c_customer_sk ORDER BY c_customer_id LIMIT 100;"
   rm -f /tmp/log4j.properties
 }
@@ -672,10 +674,32 @@ collect_bigdata_omni_shuffle(){
   spark_path=$1
   shuffle_jars=$2
   database=$3
+  shuffle_ock_path=$4
+  # 自定义ock路径
   cat << EOF > /tmp/ock_spark.conf
-spark.master yarn
 spark.task.cpus 1
 spark.shuffle.compress true
+spark.shuffle.spill.compress true
+spark.rdd.compress true
+spark.executor.extraClassPath     $shuffle_jars
+spark.driver.extraClassPath       $shuffle_jars
+
+spark.driver.extraJavaOptions -Djava.library.path=$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars
+spark.executor.extraJavaOptions -Djava.library.path=$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars
+spark.driver.extraLibraryPath   $shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars:.
+spark.executor.extraLibraryPath $shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars:.
+
+spark.shuffle.manager              org.apache.spark.shuffle.ock.OCKRemoteShuffleManager
+spark.shuffle.ock.manager true
+spark.shuffle.ock.home $shuffle_ock_path
+spark.shuffle.ock.version 24.0.0
+spark.shuffle.ock.binaryType linux-aarch64
+
+spark.blacklist.enabled true
+spark.files.fetchFailure.unRegisterOutputOnHost true
+spark.shuffle.service.enabled  false
+spark.blacklist.application.fetchFailure.enabled true
+spark.serializer                        org.apache.spark.serializer.KryoSerializer
 EOF
   timeout 20 $spark_path/bin/spark-sql --deploy-mode client --driver-cores 8 --driver-memory 40G --num-executors 24 --executor-cores 12 --executor-memory 25g --master yarn --conf spark.sql.codegen.wholeStage=false --jars $shuffle_jars --properties-file /tmp/ock_spark.conf --database $database > $log_path/bigdata_omni_shuffle.log 2>&1
   rm -f /tmp/ock_spark.conf
@@ -824,6 +848,7 @@ main(){
           zookeeper_address=$(acquire_value Bigdata zookeeper_address)
           zookeeper_path=$(acquire_value Bigdata zookeeper_path)
           shuffle_jars=$(acquire_value Bigdata shuffle_jars)
+          shuffle_ock_path=$(acquire_value Bigdata shuffle_ock_path)
           collect_bigdata_components $spark_path
           collect_bigdata_kal "${algorithms_list[@]}" $algorithms_path "${dataset_list[@]}"
           collect_bigdata_operator $spark_path $database $omnioperator_dir
@@ -831,7 +856,7 @@ main(){
           collect_bigdata_tune_up $omniadvisor_dir $mysql_username $mysql_password $mysql_database_name
           collect_bigdata_omnimv "$omnimv_dir"
           collect_bigdata_omni_push_down "$omnidata_launcher_server" "$omnidata_launcher" "$push_down_jars" "$push_down_conf" "$spark_path" "$database" "$omnidata_install_path" "$zookeeper_address" "$zookeeper_path"
-          collect_bigdata_omni_shuffle "$spark_path" "$shuffle_jars" "$database"
+          collect_bigdata_omni_shuffle "$spark_path" "$shuffle_jars" "$database" "$shuffle_ock_path"
           echo "Bigdata collect msg Done..."
       elif [ $per_project = "Virtual" ];
       then
@@ -886,4 +911,3 @@ tar_log_file $customer_information
 
 
 
-
-- 
Gitee


From 44cc1ec7f86e2d65a76bbbaab1604028da6fdcf1 Mon Sep 17 00:00:00 2001
From: ksun <sunkai71@huawei.com>
Date: Fri, 6 Sep 2024 02:56:17 +0000
Subject: [PATCH 2/4] =?UTF-8?q?=E9=87=87=E9=9B=86=E5=B7=A5=E5=85=B7=20?=
 =?UTF-8?q?=E6=96=B0=E5=A2=9E=20config.ini=20=E6=98=93=E7=94=A8=E6=80=A7?=
 =?UTF-8?q?=E8=AF=B4=E6=98=8E?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: ksun <sunkai71@huawei.com>
---
 tools/collect_msg.sh | 1295 +++++++++++++-----------------------------
 1 file changed, 394 insertions(+), 901 deletions(-)

diff --git a/tools/collect_msg.sh b/tools/collect_msg.sh
index 113d2d8..ed50b75 100644
--- a/tools/collect_msg.sh
+++ b/tools/collect_msg.sh
@@ -1,913 +1,406 @@
-#!/bin/bash
-current_path=$(pwd)
-config_file=$current_path/config.ini
-log_path=$current_path/log
-default_project="Bigdata Database Storage Arm Virt Acclib Virtual HPC"
-
-
-
-
-
-#####################根据section以及key值获取对应value############
-acquire_value(){
-    project=$1
-    key=$2
-    opt="{sub(/$key=/,\"\")}1"
-    grep $project -A 100  $config_file |grep -m 1 "$key="|awk $opt
-}
-
-
-######################获取配置文件中选择校验的解决方案###########
-acquire_select_project(){
-    all_name=""
-	for per_project in $default_project
-	do
-		status=$(acquire_value $per_project check)
-		if [[ $status = True ]]; then
-			all_name="$all_name $per_project"
-        fi
-	done
-	echo $all_name
-}
-
-
-check_customer_info(){
-  customer_information=$1
-  if [  -z "$customer_information" ];
-  then
-    echo "请您在config.ini Global字段 填写唯一个人标识 eg: xxx有限公司"
-    exit 1
-  fi
-
-  if [[ "$customer_information"x =~ "xxx有限公司" ]];
-  then
-    echo "请您在config.ini Global字段 修改 xxx有限公司为具体公司名称以供标识"
-    exit 1
-  fi
-}
-
-
-####################打包日志文件############################
-tar_log_file(){
-  customer_information=$1
-  datatime=$(date '+%Y%m%d%H%M')
-
-  if test -d $log_path;
-  then
-      echo "customer_information: ${customer_information}_isv_msg_${datatime}.tar.gz" >> $log_path/os_msg.log
-      tar zcvf ${customer_information}_isv_msg_${datatime}.tar.gz -C $log_path .
-  else
-      echo "$log_path logpath abnormality, please check"
-  fi
-}
-
-
-###################arm原生特性信息收集#################
-collect_arm_native(){
-     kbox_container=$1
-     video_container=$2
-     instruction_container=$3
-     # check tested container whether exist
-     containers=($1 $2 $3)
-     for i in ${containers[@]};do
-	     docker ps -a | grep -wq $i || { echo "the $i container doesn't found,please check!"; exit 1; }
-     done
-     # kbox基础云手机
-     rm -f $log_path/arm_native.log
-
-     keyword=(gralloc.kbox.so audio.primary.kbox.so gps.kbox.so sensors.kbox.so libmedia_omxcore.so libstagefrighthw.so vinput hwcomposer.kbox.so)
-     docker exec -it $kbox_container lsof > $log_path/arm_native_raw.log
-     for i in "${keyword[@]}";do
-	     grep -F "${i}" $log_path/arm_native_raw.log >> $log_path/arm_native.log
-     done
-     rm -f $log_path/arm_native_raw.log
-
-     docker exec -it $kbox_container cat /proc/sys/fs/binfmt_misc/ubt_a32a64 >> $log_path/arm_native.log
-     # 视频流
-     docker exec -it $video_container lsof | grep VmiInputFlinger >> $log_path/arm_native.log
-     # 指令流
-     docker exec -it $instruction_container ps -ef | grep -F "VmiAgent instruction" >> $log_path/arm_native.log
-}
-
-
-#################虚拟化特性信息收集##################
-collect_virtual_host(){
-    sudo systemctl status waasagent.service |grep "Active" > $log_path/virtual_sense.log
-    waasctl --version >> $log_path/virtual_sense.log
-
-    ovs_appctl_res=$(ovs-appctl --version 2>&1)
-
-    if [[ $ovs_appctl_res =~ "command not found" ]];
-    then
-        echo "ovs-appctl: command not found" > $log_path/virtual_dpu_flow.log
-    else
-        echo "ovs-appctl version: $ovs_appctl_res" > $log_path/virtual_dpu_flow.log
-		script -a -c 'ovs-appctl hwoff/dump-hwoff-flows' $log_path/virtual_dpu_flow.log
-    fi
-}
-
-
-collect_virtual_dpu(){
-    server_name=$1
-    network=$2
-    flavor=$3
-    volume=$4
-	availability_zone=$5
-
-    # 需要再DPU测执行
-    dpak_ovs_ctl_res=$(dpak-ovs-ctl -h 2>&1)
-    if [[ $dpak_ovs_ctl_res =~ "command not found" ]];
-    then
-        echo "请确定已在DPU测执行该工具"
-        echo "dpak_ovs_ctl: command not found" > $log_path/virtual_dpu.log
-    else
-        echo "dpak_ovs_ctl version: $dpak_ovs_ctl_res" > $log_path/virtual_dpu.log
-		script -a -c 'dpak-ovs-ctl hwoff/dump-hwoff-flows' $log_path/virtual_dpu.log
-    fi
-
-	  /usr/libexec/spdk/scripts/hw_dpu_rpc.py get_version >> $log_path/virtual_dpu.log 2>&1
-    /usr/libexec/spdk/scripts/hw_dpu_rpc.py get_controllers >> $log_path/virtual_dpu.log 2>&1
-
-    # 创建虚机
-    openstack_res=$(openstack --version 2>&1)
-
-    if [[ $openstack_res =~ "command not found" ]];
-    then
-        echo "请确定已在DPU测执行该工具"
-        echo "openstack: command not found" >> $log_path/virtual_dpu.log
-    else
-        echo "openstack version: $openstack_res" >> $log_path/virtual_dpu.log
-        openstack server create $server_name --network $network --flavor $flavor --volume $volume --availability-zone $availability_zone >> $log_path/virtual_dpu.log
-		echo "等待虚机创建完成"
-        sleep 120
-        echo "server_name: $server_name" >> $log_path/virtual_dpu.log
-        openstack server list >> $log_path/virtual_dpu.log
-    fi
-}
-
-
-collect_virtual_ceph(){
-  vm_ip=$1
-  vm_user=$2
-  vm_password=$3
-  vm_ceph_disk_name=$4
-  vm_name=$5
-  set -x
-  sshpass -p "$vm_password" ssh "$vm_user"@"$vm_ip" ls -la /sys/block/ | grep $vm_ceph_disk_name | tail -n 1 > $log_path/virtual_ceph_disk.log
-  virsh dumpxml $vm_name > $log_path/virtual_ceph_vm_xml.log
-  rpc vhost_get_controllers > $log_path/virtual_ceph_vm_controllers.log
-  rpc bdev_get_bdevs > $log_path/virtual_ceph_bdev.log
-}
-
-
-collect_virtual_ovs_xpf(){
-  ovs-appctl hwoff/dump-hwoff-flows > $log_path/virtual_ovs_xpf.log
-  echo $? >> $log_path/virtual_ovs_xpf.log
-}
-
-
-################数据库特性信息收集##################
-collect_database(){
-   mysql_install_path=$1
-   mysql_username=$2
-   mysql_password=$3
-   mysql_port=$4
-   database_name=$5
-   nvme_name=$6
-   plugin_path=$1/lib/plugin
-   timeout=60
-   $mysql_install_path/bin/mysqld_safe --defaults-file=/etc/my.cnf &
-   # 循环判断进程是否启动
-   for ((i=0; i<=$timeout; i++)); do
-     if ps -ef | grep -v grep | grep "mysql" > /dev/null; then
-       echo "Process mysql started."
-       # 执行下一步操作
-       sleep 5
-       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "select * from INFORMATION_SCHEMA.plugins where PLUGIN_NAME like 'thread_pool%'" > $log_path/database_mysql_thread_pool.log
-       echo thread_pool: $(ls $plugin_path |grep thread_pool.so) >> $log_path/database_mysql_thread_pool.log
-       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "show variables like 'thread_pool%'" > $log_path/database_mysql_thread_pool_variable.log
-       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "select * from INFORMATION_SCHEMA.plugins where PLUGIN_NAME like 'kovae%'" >> $log_path/database_mysql.log
-       echo kovae_path: $(ls $plugin_path |grep ha_kovae.so) >>  $log_path/database_mysql.log
-       readelf -a $mysql_install_path/bin/mysqld|grep bolt >> $log_path/database_mysql.log
-       echo no_lock: $(objdump -d $mysql_install_path/bin/mysqld|grep -c row_vers_build_for_semi_consistent_readP5trx_t) >> $log_path/database_mysql.log
-       objdump -d $mysql_install_path/bin/mysqld |grep crc32cb >> $log_path/database_mysql.log
-       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "show variables like '%paralle%'" >> $log_path/database_mysql.log
-       nm $mysql_install_path/bin/mysqld | grep -c Page_shards >> $log_path/database_mysql_page_shards.log
-       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "show variables like 'sched_affinity%'" >> $log_path/database_mysql.log
-       hioadm atomicwrite -d $nvme_name > $log_path/database_mysql_nvme.log
-       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "show variables like '%flush_method%'" >> $log_path/database_mysql_nvme.log
-       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "show variables like '%doublewrite%'" >> $log_path/database_mysql_nvme.log
-       gazellectl lstack show 1 -c | grep ":$mysql_port" > $log_path/database_mysql_gazelle.log
-       pkill -9 mysql
-       break
-     fi
-     sleep 1
-     if [ $timeout -eq $i ];then
-       echo "Timeout error: mysql process not started in $timeout seconds.i"
-       exit 1
-     fi
-   done
-}
-
-
-collect_database_other_db(){
-  other_db_bin=$1
-  greenplum_username=$2
-  greenplum_port=$3
-  kae_version=$4
-  greenplum_kae_sql=$5
-  readelf -a $other_other_db_bin | grep bolt > $log_path/database_other_db.log
-  objdump -d $other_other_db_bin | grep crc32cb >> $log_path/database_other_db.log
-  if [ "$kae_version" == "1.0" ]; then
-    nohup timout 20 watch -gt -n 0.2 cat /sys/class/uacce/hisi_zip*/attrs/available_instances > $log_path/database_greenplum_kae.log &
-  else
-    nohup timeout 20 watch -gt -n 0.2 cat /sys/class/uacce/hisi_zip*/available_instances > $log_path/database_greenplum_kae.log &
-  fi
-  psql -h 127.0.0.1 -p $greenplum_port -U $greenplum_username -c "$greenplum_kae_sql"
-}
-
-
-####################机密计算特性信息收集################
-collect_virtcca_msg(){
-		cvm_name=$1
-	username=$2
-	passwd=$3
-	xml_path=/tmp/temp.xml
-	virsh list --all|grep -q $cvm_name
-	if [ $? -ne 0 ]; then
-    		echo "错误：虚拟机 $cvm_name 不存在"
-    		return 0
-	fi
-	vm_status=$(virsh domstate "$cvm_name")
-
-	if [ "$vm_status" == "shut off" ]; then
-    		echo "虚拟机 $cvm_name 处于 shut off 状态，正在启动..."
-    		virsh start "$cvm_name"
-    		echo "虚拟机 $cvm_name 启动完成"
-	elif [ "$vm_status" == "running" ]; then
-    		echo "虚拟机 $cvm_name 处于 running 状态，无需操作"
-	else
-    		echo "错误：无法确定虚拟机 $cvm_name 的状态"
-   	        return 0
-	fi
-
-	virsh dumpxml $cvm_name > $xml_path
-	ret=$(grep -i "type='cvm'" $xml_path)
-	echo "$ret" > $log_path/virtcca_status.log
-	expect << EOF >> $log_path/virtcca_status.log
-        spawn virsh console $cvm_name
-        expect "Escape character is \\^]"
-        send "\r"
-        expect "login:"
-        send "$username\r"
-        expect "Password:"
-        send "$passwd\r"
-	expect "# "
-	send "ls -l /\r"
-	expect "# "
-	send "exit\r"
-	expect eof
-EOF
-}
-
-
-collect_ccos_msg(){
-    /vendor/bin/tee-check > $log_path/virtccos_itrustee.log
-    tlogcat -f &
-    sleep 3s
-    cat /var/log/tee/teeOS_log-0  | grep UUID >> $log_path/virtccos_itrustee.log
-    ps aux | grep tlogcat | awk '{print $2}' | xargs kill
-}
-
-
-#################加速库特性信息收集##################
-collect_acceleration_library(){
-    system_lib=$1
-    hmpp_lib=$2
-    math_lib=$3
-    math_jar=$4
-    math_java=$5
-    openssl speed -elapsed -engine kae rsa2048  > $log_path/acceleration_library.log 2>&1
-    ldd $1 >> $log_path/acceleration_library.log
-    ldd $2 >> $log_path/acceleration_library.log
-    ldd $3 >> $log_path/acceleration_library.log
-    jar -tf $4 >> $log_path/acceleration_library_kml_java.log
-    javap -v $5 >> $log_path/acceleration_library_kml_java.log
-}
-
-
-###############分布式存储特性信息收集###############
-# $1 ec_pool 名字
-collect_storage_acc(){
-    ec_pool=$1
-    ceph_conf=$2
-    storage_maintain_bin=$3
-    rocksdb_bin=$4
-    ucache_bin=$5
-    non_ceph_bin=$6
-    non_ceph_pid=$7
-    # 存储加速库
-    ldd /usr/bin/ceph-osd > $log_path/storage_acc.log
-    bcache_dev=$(ls /sys/class/block|grep -m 1 bcache)
-    # 如果没有课增加异常判断
-    ls -l /sys/class/block/$bcache_dev/bcache/cache/internal/traffic_policy_start >> $log_path/storage_acc.log
-
-    pool_list=$(sudo rados lspools |grep -wx $ec_pool)
-    if [[ $pool_list =~ $ec_pool ]];
-    then
-	      echo "ec_pool created" >> $log_path/storage_acc.log
-	      pid_num=$(ps -ef|grep  osd|grep -v grep|head -n 1|awk '{print $2}')
-	      sudo cat /proc/$pid_num/smaps |grep ksal >> $log_path/storage_acc.log
-    else
-	      echo "ec_pool not exist" >> $log_path/storage_acc.log
-    fi
-
-    systemctl status ceph-boost.service > $log_path/storage_io.log
-    if ceph osd pool set vdbench compression_algorithm glz; then
-      \cp "$ceph_conf" "$ceph_conf".bak
-      sed -i '/^compressor_glz_level/d' "$ceph_conf"
-      echo "compressor_glz_level = 1" >> "$ceph_conf"
-      systemctl restart ceph.target
-      systemctl status ceph.target > $log_path/storage_comporess.log
-      \cp "$ceph_conf".bak "$ceph_conf"
-    fi
-    ldd $storage_maintain_bin > $log_path/storage_maintain_tool.log
-    lib_rocksdb=$(ldd $rocksdb_bin | grep librocksdb | awk '{print $3}')
-    ldd $lib_rocksdb > $log_path/storage_rocksdb.log
-    ldd $ucache_bin > $log_path/storage_ucache.log
-
-    if ldd $non_ceph_bin | grep ksal; then
-      timeout 20 perf top -p $non_ceph_pid > $log_path/storage_non_ceph_perf_top.log
-    fi
-}
-
-
-###############大数据特性信息收集##################
-collect_bigdata_kal(){
-  algotithm_list=$1
-  algotithm_path=$2
-  dataset_list=$3
-
-  read -r -a  algotithm_arry <<< "$algotithm_list"
-  read -r -a  dataset_arry <<< "$dataset_list"
-
-  cd $algotithm_path
-  index=0
-  for per_alg in ${algotithm_list[*]}
-  do
-      # "Usage: <dataset name> <is raw> <is check>","1st argument: name of dataset: cit_patents, enwiki_2018, uk_2002","2nd argument: optimization algorithm or raw: no/yes","3rd argument: verify result: no/yes"
-      if [ "$per_alg" == "betweenness" ] || [ "$per_alg" == "node2vec" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage:<dataset name> <is raw>","1st argument: name of dataset: cit_patents,enwiki_2018,arabic_2005,graph500_22,graph500_23,graph500_25","2nd argument: optimization algorithm or raw: no/yes"
-      if [ "$per_alg" == "bfs" ] || [ "$per_alg" == "cc" ] || [ "$per_alg" == "deepwalk" ] || [ "$per_alg" == "diameter" ] || [ "$per_alg" == "ecc" ] || [ "$per_alg" == "fraudar" ] || [ "$per_alg" == "katz" ] || [ "$per_alg" == "kcore" ] || [ "$per_alg" == "ktruss" ] || [ "$per_alg" == "louvain" ] || [ "$per_alg" == "modularity" ] || [ "$per_alg" == "mst" ] || [ "$per_alg" == "scc" ] || [ "$per_alg" == "slpa" ] || [ "$per_alg" == "tpr" ] || [ "$per_alg" == "trussdecomposition" ] || [ "$per_alg" == "wlpa" ] || [ "$per_alg" == "wmssp" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage:<dataset name>","dataset name: simulate1,simulate2,usaRoad"
-      if [ "$per_alg" == "cd" ] || [ "$per_alg" == "inccc" ] || [ "$per_alg" == "mce" ] || [ "$per_alg" == "wce" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <weight or not> <isRaw>","1st argument: name of dataset: name of dataset: cit_patents,uk_2002","2nd argument: weight or not: e.g. weighted,unweighted","3rd argument: verify result: no/yes"
-      if [ "$per_alg" == "closeness" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} weight no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <api name> <weight or not> <isRaw>","1st argument: name of dataset: name of dataset: cit_patents,uk_2002,arabic_2005,graph500_22,graph500_23,graph500_24,graph500_25"
-      # "2nd argument: name of api: lcc,avgcc,globalcc","3nd argument: weight or not: weighted,unweighted","4th argument: optimization algorithm or raw: no/yes"
-      if [ "$per_alg" == "clusteringcoefficient" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} lcc weighted no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <api name> <isRaw>","1st argument: name of dataset: it_2004,twitter7,uk_2007_05,mycielskian20,gap_kron,com_friendster"
-      # "2nd argument: name of api: degrees,inDegrees,outDegrees","3rd argument: optimization algorithm or raw: no/yes"
-      if [ "$per_alg" == "degree" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} degrees no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <rate> <batch> <isRaw>","1st argument: name of dataset: twitter_2010","2nd argument: rate: e.g. 0.001,0.01,0.05"
-      # "3nd argument: batch: e.g. 1,2,3,4,5","4th argument: optimization algorithm or raw: no/yes"
-      if [ "$per_alg" == "incpr" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} 0.001 1 no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <queryGraph name> <identical or not>","1st argument: name of dataset: name of dataset: graph500_21,com_orkut"
-      # "2nd argument: name of queryGraph: for Identical: 4dgn/4sqr/6star; for unIdentical: 4dgn/4sqr/4clique/5clique/6clique","3rd argument: match mode:Identical,unIdentical"
-      if [ "$per_alg" == "incsgm" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} 4dgn Identical > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <api name> <isRaw>","1st argument: name of dataset: graph500_22,graph500_24,graph500_25","2nd argument: api: run,runConvergence","3rd argument: optimization algorithm or raw: no/yes"
-      if [ "$per_alg" == "lpa" ] || [ "$per_alg" == "pr" ] || [ "$per_alg" == "tc" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} run no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <source number> <isRaw>","1st argument: name of dataset: soc_liveJournal,uk_2002,arabic_2005","2nd argument: source number: 5/50","3rd argument: optimization algorithm or raw: no/yes"
-      if [ "$per_alg" == "mssp" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} 5 no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <isRaw>","1st argument: name of dataset: epinions, graph500_23_weight, graph500_25_weight","2nd argument: anomaly_type: 0/1","3rd argument: optimization algorithm or raw: no/yes"
-      if [ "$per_alg" == "oddball" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} 0 no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <api name> <isRaw> <sourceCnt>","1st argument: name of dataset: cit_patents,uk_2002,arabic_2005","2nd argument: name of api: fixMS,fixSS,conSS"
-      # "3rd argument: optimization algorithm or raw: no/yes","4th argument: sourceCnt or null: 1,5,10,50,100"
-      if [ "$per_alg" == "ppr" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} fixMS no 1 > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <queryGraph name> <identical or not> <isRaw>","1st argument: name of dataset: name of dataset: graph500_19,liveJournal,com_orkut"
-      # "2nd argument: name of queryGraph: for Identical: 4dgn/4sqr/5tree/6star; for unIdentical: 4dgn/4clique/5clique/6clique","3rd argument: match mode:Identical,unIdentical","4th argument: optimization algorithm or raw: no/yes"
-      if [ "$per_alg" == "sgm" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} 4dgn Identical no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <api name> <seeds count>","1st argument: name of dataset: cit_patents,uk_2002,arabic_2005","2nd argument: name of api: run,runUntilConvergence","3nd argument: seeds count: 100,500,1000"
-      if [ "$per_alg" == "tr" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} run 100 > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <api name> <isRaw>","1st argument: name of dataset: cage14, GAP_road, GAP_twitter","2nd argument: name of api: static, convergence","3rd argument: optimization algorithm or raw: no, yes"
-      if [ "$per_alg" == "wpr" ];
-      then
-          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} static no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <data structure> <dataset name> <api name> <isRaw> <isCheck>","1st argument: type of data structure: [dataframe/rdd]","2nd argument: name of dataset: e.g. als/alsbs/alsh"
-      # "3rd argument: name of API: e.g. fit/fit1/fit2/fit3; for rdd: train","4th argument: optimization algorithm or raw: [no/yes]","5th argument: Whether to Compare Results [no/yes]"
-      if [ "$per_alg" == "als" ] || [ "$per_alg" == "kmeans" ] || [ "$per_alg" == "lda" ] || [ "$per_alg" == "pca" ];
-      then
-          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh dataframe ${dataset_arry[$index]} fit no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <isRaw> <isCheck>","1st argument: name of dataset: e.g. CP10M1K/CP2M5K/CP1M10K","2nd argument: optimization algorithm or raw: [no/yes]","3rd argument: Whether to Compare Results [no/yes]"
-      if [ "$per_alg" == "bo" ] || [ "$per_alg" == "cov" ] || [ "$per_alg" == "crf" ] || [ "$per_alg" == "encoder" ] || [ "$per_alg" == "fpg" ] || [ "$per_alg" == "hdb" ] || [ "$per_alg" == "idf" ] || [ "$per_alg" == "if" ] || [ "$per_alg" == "nmf" ] || [ "$per_alg" == "ps" ] || [ "$per_alg" == "simrank" ] || [ "$per_alg" == "svd" ] || [ "$per_alg" == "te" ];
-      then
-          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <isRaw>","1st argument: name of dataset: e.g. bremenSmall/farm/house","2nd argument: optimization algorithm or raw: [no/yes]"
-      if [ "$per_alg" == "dbscan" ] || [ "$per_alg" == "knn" ];
-      then
-          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <algorithm type> <data structure> <dataset name> <api name> <isRaw> <ifCheck>","1st argument: type of algorithm: [classification/regression]","2nd argument: type of data structure: [dataframe/rdd]"
-      # "3rd argument: name of dataset: [epsilon/higgs/mnist8m]","4th argument: name of API: [for dataframe: fit/fit1/fit2/fit3; for rdd: trainClassifier/trainRegressor]","5th argument: optimization algorithm or raw: [no/yes]"
-      # "6th argument: Whether to Compare Results [no/yes]"
-      if [ "$per_alg" == "dt" ] || [ "$per_alg" == "gbdt" ] || [ "$per_alg" == "rf" ];
-      then
-          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh classification dataframe ${dataset_arry[$index]} fit no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <api name> <save or verify> <isRaw>","1st argument: name of dataset: higgs/mnist8m","2nd argument: name of API: fit/fit1/fit2/fit3"
-      # "3rd argument: save or verify result: save/verify","4th argument: optimization algorithm or raw: no/yes"
-      if [ "$per_alg" == "dtb" ];
-      then
-          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} fit verify no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <algorithm type> <data structure> <dataset name> <api name> <isRaw> <isCheck>","1st argument: type of algorithm: [classification/regression]"
-      # "2nd argument: name of dataset: [higgs/avazu]","3rd argument: name of API: [fit]"
-      # "4th argument: optimization algorithm or raw: [no/yes]","5th argument: Whether to Compare Results [no/yes]"
-      if [ "$per_alg" == "fm" ];
-      then
-          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh classification ${dataset_arry[$index]} fit no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <algorithm type> <dataset name> <isRaw> <isCheck>","1st argument: type of algorithm: [classification/regression]","2nd argument: name of dataset:mnist8m, higgs "
-      # "3rd argument: optimization algorithm or raw: [no/yes]","4th argument: Whether to Compare Results [no/yes]"
-      if [ "$per_alg" == "lgbm" ];
-      then
-          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh classification ${dataset_arry[$index]} no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <api name> <isRaw> <isCheck>","1st argument: name of dataset: e.g. mnist8m/Twitter/rcv"
-      # "2nd argument: name of API: e.g. fit/fit1/fit2/fit3","3th argument: optimization algorithm or raw: [no/yes]","4th argument: Whether to Compare Results [no/yes]"
-      if [ "$per_alg" == "linR" ] || [ "$per_alg" == "logR" ] || [ "$per_alg" == "spca" ] || [ "$per_alg" == "svm" ];
-      then
-          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} fit no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <data structure> <dataset name> <isRaw> <isCheck>","1st argument: type of data structure: [dataframe/rdd]","2nd argument: name of dataset: e.g. CP10M1K/CP2M5K/CP1M10K"
-      # "3nd argument: optimization algorithm or raw: [no/yes]","4rd argument: Whether to Compare Results [no/yes]"
-      if [ "$per_alg" == "pearson" ] || [ "$per_alg" == "spearman" ];
-      then
-          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh dataframe ${dataset_arry[$index]} no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <api name> <isRaw>","1st argument: name of dataset: cate/node/item/taobao","2nd argument: name of API: fit/fit1/fit2/fit3","3rd argument:optimization algorithm or raw: no/yes"
-      if [ "$per_alg" == "word2vec" ];
-      then
-          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} fit no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      # "Usage: <dataset name> <algorithm type> <isRaw> <isCheck>","1rd argument: name of dataset: e.g. higgs/mnist8m","2st argument: type of algorithm: [classification/regression]"
-      # "3th argument: optimization algorithm or raw: [no/yes]","4th argument: Whether to Compare Results [no/yes]"
-      if [ "$per_alg" == "xgbt" ];
-      then
-          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} classification no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
-      fi
-      index=`expr $index + 1`
-  done
-
-}
-
-
-collect_bigdata_operator(){
-        # 日志记录位置 log_path/bigdata_operator.log
-	spark_path=$1
-	database=$2
-    omnioperator_dir=$3
-	if [ -e $spark_path ] && [ -e $omnioperator_dir ];
-	then
-        spark_version=`awk '{print $2}' $spark_path/RELEASE | head -n 1`
-        omnioperator_version=`cat $omnioperator_dir/version.txt | grep 'Component Version' | awk -F ": " '{print $2}'`
-        echo "spark version:$spark_version omnioperator version:$omnioperator_version" >$log_path/bigdata_operator.log 2>&1
-        spark_omni_func=(
-        --deploy-mode client
-        --driver-cores 5
-        --driver-memory 5g
-        --num-executors 6
-        --executor-cores 2
-        --executor-memory 6g
-        --master yarn
-        --conf spark.memory.offHeap.enabled=true
-        --conf spark.memory.offHeap.size=18g
-        --conf spark.task.cpus=1
-        --conf spark.driver.extraClassPath=${omnioperator_dir}/lib/boostkit-omniop-spark-${spark_version}-${omnioperator_version}-aarch64.jar:${omnioperator_dir}/lib/boostkit-omniop-bindings-${omnioperator_version}-aarch64.jar:${omnioperator_dir}/lib/dependencies/*
-        --conf spark.executor.extraClassPath=${omnioperator_dir}/lib/boostkit-omniop-spark-${spark_version}-${omnioperator_version}-aarch64.jar:${omnioperator_dir}/lib/boostkit-omniop-bindings-${omnioperator_version}-aarch64.jar:${omnioperator_dir}/lib/dependencies/*
-        --driver-java-options -Djava.library.path=${omnioperator_dir}/lib
-        --conf spark.sql.codegen.wholeStage=false
-        --conf spark.executorEnv.LD_LIBRARY_PATH=${omnioperator_dir}/lib
-        --conf spark.executorEnv.OMNI_HOME=${omnioperator_dir}/
-        --conf spark.driverEnv.LD_LIBRARY_PATH=${omnioperator_dir}/lib
-        --conf spark.driverEnv.OMNI_HOME=${omnioperator_dir}/
-        --conf spark.executor.extraLibraryPath=${omnioperator_dir}/lib
-        --conf spark.driverEnv.LD_PRELOAD=${omnioperator_dir}/lib/libjemalloc.so.2
-        --conf spark.executorEnv.LD_PRELOAD=${omnioperator_dir}/lib/libjemalloc.so.2
-        --conf spark.sql.extensions=com.huawei.boostkit.spark.ColumnarPlugin
-        --jars ${omnioperator_dir}/lib/boostkit-omniop-spark-${spark_version}-${omnioperator_version}-aarch64.jar
-        --jars ${omnioperator_dir}/lib/boostkit-omniop-bindings-${omnioperator_version}-aarch64.jar
-        --conf spark.sql.orc.impl=native
-        --conf spark.shuffle.manager=org.apache.spark.shuffle.sort.OmniColumnarShuffleManager
-        --conf spark.omni.sql.columnar.fusion=false
-        --conf spark.omni.sql.columnar.sortSpill.enabled=true
-        --conf spark.omni.sql.columnar.sortSpill.rowThreshold=4000000
-        --conf spark.omni.sql.columnar.sortSpill.dirDiskReserveSize=214748364800
-        --conf spark.locality.wait=8
-        --conf spark.sql.autoBroadcastJoinThreshold=10M
-        --conf spark.sql.broadcastTimeout=500
-        --conf spark.sql.cbo.enabled=false
-        --conf spark.default.parallelism=200
-        --conf spark.sql.shuffle.partitions=200
-        --conf spark.executorEnv.MALLCO_CONF=narenas:2
-)
-
-	    spark_conf_path=$1/conf
-        if [ X"${spark_version}" == "X3.1.1" ];then
-            if [ ! -f $spark_conf_path/log4j.properties ];then
-                cp $spark_conf_path/log4j.properties.template $spark_conf_path/log4j.properties
-            fi
-            if ! cat < $spark_conf_path/log4j.properties|grep "^log4j.logger.com.huawei.boostkit.spark=INFO";
-            then
-                    echo "log4j.logger.com.huawei.boostkit.spark=INFO" >> $spark_conf_path/log4j.properties
-            fi
-        elif [ X"${spark_version}" == "X3.3.1" ];then
-            if [ ! -f $spark_conf_path/log4j2.properties ];then
-                cp $spark_conf_path/log4j2.properties.template $spark_conf_path/log4j2.properties
-            fi
-            sed -i "s/^logger.thriftserver.level =.*/logger.thriftserver.level = INFO/" $spark_conf_path/log4j2.properties
-        else
-            echo "Spark ${spark_version} is not supported." >>$log_path/bigdata_operator.log 2>&1
-        fi
-	    $spark_path/bin/spark-sql "${spark_omni_func[@]}" --database $database -e "WITH customer_total_return AS ( SELECT sr_customer_sk AS ctr_customer_sk, sr_store_sk AS ctr_store_sk, sum(sr_return_amt) AS ctr_total_return FROM store_returns, date_dim WHERE sr_returned_date_sk = d_date_sk AND d_year = 2000 GROUP BY sr_customer_sk, sr_store_sk) SELECT c_customer_id FROM customer_total_return ctr1, store, customer WHERE ctr1.ctr_total_return > (SELECT avg(ctr_total_return) * 1.2 FROM customer_total_return ctr2 WHERE ctr1.ctr_store_sk = ctr2.ctr_store_sk) AND s_store_sk = ctr1.ctr_store_sk AND s_state = 'TN' AND ctr1.ctr_customer_sk = c_customer_sk ORDER BY c_customer_id LIMIT 100;" 1>>$log_path/bigdata_operator.log 2>&1
-	else
-	    echo "$spark_path or $omnioperator_dir does not exist" >$log_path/bigdata_operator.log 2>&1
-	fi
-}
-
-
-collect_bigdata_hbase(){
-
-   hbase com.huawei.boostkit.hindex.mapreduce.GlobalTableIndexer -Dtablename.to.index=OnlySingleIndexTable -Dindexspecs.to.addandbuild='osindex=>C0:[F1]'
-   hbase shell << EOF > $log_path/bigdata_hbase.log 2>&1
-   debug
-   scan 'OnlySingleIndexTable',{FILTER=>"(SingleColumnValueFilter('C0', 'F1',=,'binary:bbb')"}
-   exit
-EOF
-}
-
-
-collect_bigdata_tune_up(){
-   omniadvisor_dir=$1
-   mysql_username=$2
-   mysql_password=$3
-   mysql_database=$4
-   if [ -e $omniadvisor_dir/omniadvisor ];
-   then
-       echo "omniadvisor.log" >> $log_path/bigdata_tune_up.log
-   else
-      echo "omniadvisor.log not exist" >> $log_path/bigdata_tune_up.log
-   fi
-
-   mysql -u $mysql_username -p$mysql_password -D $mysql_database  -e "show tables" >> $log_path/bigdata_tune_up.log 2>&1
-
-}
-
-
-collect_bigdata_omnimv(){
-  omnimv_dir=$1
-  hdfs dfs -ls $omnimv_dir > $log_path/bigdata_omnimv.log
-}
-
-
-collect_bigdata_omni_push_down(){
-  omnidata_launcher_server=$1
-  omnidata_launcher=$2
-  push_down_jars=$3
-  push_down_conf=$4
-  spark_path=$5
-  database=$6
-  omnidata_install_path=$7
-  zookeeper_address=$8
-  zookeeper_path=$9
-
-  if [  -z "$omnidata_launcher_server" ]; then
-    sh $omnidata_launcher status > $log_path/bigdata_omni_launcher_status.log
-  else
-    ssh $omnidata_launcher_server sh $omnidata_launcher status > $log_path/bigdata_omni_launcher_status.log
-  fi
-  cat << EOF > /tmp/log4j.properties
-log4j.rootCategory=INFO, FILE
-log4j.appender.console=org.apache.log4j.ConsoleAppender
-log4j.appender.console.target=System.err
-log4j.appender.console.layout=org.apache.log4j.PatternLayout
-log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n
-
-log4j.logger.org.apache.spark.sql.execution=DEBUG
-log4j.logger.org.apache.spark.repl.Main=INFO
-
-log4j.appender.FILE=org.apache.log4j.FileAppender
-log4j.appender.FILE.file=$log_path/bigdata_omni_push_down.log
-log4j.appender.FILE.layout=org.apache.log4j.PatternLayout
-
-log4j.appender.FILE.layout.ConversionPattern=%m%n
-EOF
-  # 这里直接用 operator 的采集 sql
-  $spark_path/bin/spark-sql --driver-class-path "$push_down_jars" --jars "$push_down_jars" \
-  --conf "$push_down_conf" \
-  --conf spark.sql.cbo.enabled=true \
-  --conf spark.sql.cbo.planStats.enabled=true \
-  --conf spark.sql.ndp.enabled=true \
-  --conf spark.sql.ndp.filter.selectivity.enable=true \
-  --conf spark.sql.ndp.filter.selectivity=0.5 \
-  --conf spark.sql.ndp.alive.omnidata=3 \
-  --conf spark.sql.ndp.table.size.threshold=10 \
-  --conf spark.sql.ndp.zookeeper.address=$zookeeper_address \
-  --conf spark.sql.ndp.zookeeper.path=$zookeeper_path \
-  --conf spark.sql.ndp.zookeeper.timeout=15000 \
-  --conf spark.driver.extraLibraryPath=$omnidata_install_path/haf-host/lib \
-  --conf spark.executor.extraLibraryPath=$omnidata_install_path/haf-host/lib \
-  --conf spark.executorEnv.HAF_CONFIG_PATH=$omnidata_install_path/haf-host/etc/ \
-  --name tpcds_test.sql --driver-memory 50G --driver-java-options -Dlog4j.configuration=file:/tmp/log4j.properties \
-  --executor-memory 32G --num-executors 30 --executor-cores 18 --database $database \
-  -e "WITH customer_total_return AS ( SELECT sr_customer_sk AS ctr_customer_sk, sr_store_sk AS ctr_store_sk, sum(sr_return_amt) AS ctr_total_return FROM store_returns, date_dim WHERE sr_returned_date_sk = d_date_sk AND d_year = 2000 GROUP BY sr_customer_sk, sr_store_sk) SELECT c_customer_id FROM customer_total_return ctr1, store, customer WHERE ctr1.ctr_total_return > (SELECT avg(ctr_total_return) * 1.2 FROM customer_total_return ctr2 WHERE ctr1.ctr_store_sk = ctr2.ctr_store_sk) AND s_store_sk = ctr1.ctr_store_sk AND s_state = 'TN' AND ctr1.ctr_customer_sk = c_customer_sk ORDER BY c_customer_id LIMIT 100;"
-  rm -f /tmp/log4j.properties
-}
-
-
-collect_bigdata_omni_shuffle(){
-  spark_path=$1
-  shuffle_jars=$2
-  database=$3
-  shuffle_ock_path=$4
-  # 自定义ock路径
-  cat << EOF > /tmp/ock_spark.conf
-spark.task.cpus 1
-spark.shuffle.compress true
-spark.shuffle.spill.compress true
-spark.rdd.compress true
-spark.executor.extraClassPath     $shuffle_jars
-spark.driver.extraClassPath       $shuffle_jars
-
-spark.driver.extraJavaOptions -Djava.library.path=$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars
-spark.executor.extraJavaOptions -Djava.library.path=$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars
-spark.driver.extraLibraryPath   $shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars:.
-spark.executor.extraLibraryPath $shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars:.
-
-spark.shuffle.manager              org.apache.spark.shuffle.ock.OCKRemoteShuffleManager
-spark.shuffle.ock.manager true
-spark.shuffle.ock.home $shuffle_ock_path
-spark.shuffle.ock.version 24.0.0
-spark.shuffle.ock.binaryType linux-aarch64
-
-spark.blacklist.enabled true
-spark.files.fetchFailure.unRegisterOutputOnHost true
-spark.shuffle.service.enabled  false
-spark.blacklist.application.fetchFailure.enabled true
-spark.serializer                        org.apache.spark.serializer.KryoSerializer
-EOF
-  timeout 20 $spark_path/bin/spark-sql --deploy-mode client --driver-cores 8 --driver-memory 40G --num-executors 24 --executor-cores 12 --executor-memory 25g --master yarn --conf spark.sql.codegen.wholeStage=false --jars $shuffle_jars --properties-file /tmp/ock_spark.conf --database $database > $log_path/bigdata_omni_shuffle.log 2>&1
-  rm -f /tmp/ock_spark.conf
-}
-
-
-collect_bigdata_components(){
-  spark_path=$1
-  $spark_path/bin/spark-sql --version && echo spark > $log_path/bigdata_components.log
-  hive --version && echo hive >> $log_path/bigdata_components.log
-  hbase version && echo hbase >> $log_path/bigdata_components.log
-}
-
-
-#################HPC特性信息收集##################
-# $1 #用户可执行文件路径
-
-collect_hpc_acceleration_library(){
-    bin_path=$1
-    rm -rf $log_path/hpc_acceleration_library.log
-    touch $log_path/hpc_acceleration_library.log
-    ldd $bin_path > $log_path/hpc_acceleration_library.log  2>&1
-}
-
-# $1 #用户可执行文件路径
-collect_sme_acceleration_library(){
-    bin_path=$1
-    ifsme=`lscpu|grep Flags|grep sme`
-    if [ -n "$ifsme" ]; then
-        bin_path=$1 #用户可执行文件路径
-        rm -rf $log_path/hpc_SME_library.log
-        touch $log_path/hpc_SME_library.log
-        ldd $bin_path | grep SME >> $log_path/hpc_SME_library.log 2>&1
-        objdump -d $bin_path >> $log_path/hpc_SME_library.log 2>&1
-    else
-      echo "架构不支持SME" >> $log_path/hpc_SME_library.log
-    fi
-
-}
-
-collect_sve_source_code(){
-  grep -r arm_sve.h "$1" > $log_path/hpc_sve.log
-}
-
-
-################环境信息收集#######################
-collect_os_msg(){
-    echo  os: $(cat /etc/os-release |grep PRETTY_NAME=|awk -F= '{print $2}') >  $log_path/os_msg.log
-    echo kernel: $(uname -r) >> $log_path/os_msg.log
-    dmidecode -t Processor|grep -m 1 Version: >> $log_path/os_msg.log
-    dmidecode -t system|grep "Product Name" >> $log_path/os_msg.log
-  }
-
-
-main(){
-  select_project=$(acquire_select_project)
-  echo "开始收集BoostKit 特性信息如下：$select_project"
-  mkdir -p $log_path
-  rm -fr $log_path/*
-  echo "日志存放位置： $log_path"
-
-  collect_os_msg
-	for per_project in $select_project
-	do
-	    if [ $per_project = "Arm" ];
-		  then
-		    	kbox_container=$(acquire_value Arm kbox_container)
-	        video_container=$(acquire_value Arm video_container)
-	        instruction_container=$(acquire_value Arm instuction_container)
-	        echo "start collect Arm msg..."
-	        collect_arm_native $kbox_container $video_container $instruction_container
-	        echo "Arm collect msg Done..."
-	    elif [ $per_project = "Virt" ];
-		  then
-			    echo "start collect Virt msg..."
-			    cvm_name=$(acquire_value Virtcca cvm_name)
-          cvm_username=$(acquire_value Virtcca cvm_username)
-          cvm_password=$(acquire_value Virtcca cvm_password)
-          collect_ccos_msg
-          collect_virtcca_msg $cvm_name $cvm_username $cvm_password
-          echo "Virt collect msg Done..."
-		  elif [ $per_project = "Database" ];
-		  then
-		      echo "start collect Database msg..."
-		      use_mysql=$(acquire_value Database use_mysql)
-		      mysql_install_path=$(acquire_value Database mysql_install_path)
-		      mysql_username=$(acquire_value Database mysql_username)
-		      mysql_password=$(acquire_value Database mysql_password)
-		      mysql_port=$(acquire_value Database mysql_port)
-		      database_name=$(acquire_value Database database_name)
-		      nvme_name=$(acquire_value Database nvme_name)
-
-          if [ "$use_mysql" == "1" ]; then
-            collect_database  $mysql_install_path $mysql_username $mysql_password $mysql_port $database_name $nvme_name
-            echo "Database mysql collect msg Done..."
-          else
-            other_db_bin=$(acquire_value Database other_db_bin)
-            greenplum_username=$(acquire_value Database greenplum_username)
-            greenplum_port=$(acquire_value Database greenplum_port)
-            kae_version=$(acquire_value Database kae_version)
-            greenplum_kae_sql=$(acquire_value Database greenplum_kae_sql)
-            collect_database_other_db "$other_db_bin" "$greenplum_username" "$greenplum_password" "$greenplum_port" "$kae_version" "$greenplum_kae_sql"
-            echo "Database other db collect msg Done..."
-          fi
-      elif [ $per_project = "Acclib" ];
-      then
-           echo "start collect acceleration_library msg..."
-           system_lib=$(acquire_value Acclib system_lib)
-           hmpp_lib=$(acquire_value Acclib HMPP_lib)
-           math_lib=$(acquire_value Acclib math_lib)
-           math_jar=$(acquire_value Acclib math_jar)
-           math_java=$(acquire_value Acclib math_java)
-           collect_acceleration_library "$system_lib" "$hmpp_lib" "$math_lib" "$math_jar" "$math_java"
-           echo "acceleration_library collect msg Done..."
-      elif [ $per_project = "Storage" ];
-      then
-          echo "start collect Storage msg..."
-          ec_pool_name=$(acquire_value Storage ec_pool_name)
-          ceph_conf=$(acquire_value Storage ceph_conf)
-          storage_maintain_bin=$(acquire_value Storage storage_maintain_bin)
-          rocksdb_bin=$(acquire_value Storage rocksdb_bin)
-          ucache_bin=$(acquire_value Storage ucache_bin)
-          non_ceph_bin=$(acquire_value Storage non_ceph_bin)
-          non_ceph_pid=$(acquire_value Storage non_ceph_pid)
-          collect_storage_acc "$ec_pool_name" "$ceph_conf" "$storage_maintain_bin" "$rocksdb_bin" "$ucache_bin" "$non_ceph_bin" "$non_ceph_pid"
-          echo "Storage collect msg Done..."
-      elif [ $per_project = "Bigdata" ];
-      then
-          echo "start collect Bigdata msg..."
-          algorithms_path=$(acquire_value Bigdata algorithms_path)
-          algorithms_list=$(acquire_value Bigdata algorithms_name)
-          dataset_list=$(acquire_value Bigdata dataset_list)
-          spark_path=$(acquire_value Bigdata spark_path)
-          database=$(acquire_value Bigdata database)
-          omnioperator_dir=$(acquire_value Bigdata omnioperator_dir)
-          omniadvisor_dir=$(acquire_value Bigdata omniadvisor_dir)
-          mysql_username=$(acquire_value Bigdata mysql_username)
-          mysql_password=$(acquire_value Bigdata mysql_password)
-          mysql_database_name=$(acquire_value Bigdata mysql_database_name)
-          omnimv_dir=$(acquire_value Bigdata omnimv_dir)
-          omnidata_launcher=$(acquire_value Bigdata omnidata_launcher)
-          omnidata_launcher_server=$(acquire_value Bigdata omnidata_launcher_server)
-          omnidata_install_path=$(acquire_value Bigdata omnidata_install_path)
-          push_down_jars=$(acquire_value Bigdata push_down_jars)
-          push_down_conf=$(acquire_value Bigdata push_down_conf)
-          zookeeper_address=$(acquire_value Bigdata zookeeper_address)
-          zookeeper_path=$(acquire_value Bigdata zookeeper_path)
-          shuffle_jars=$(acquire_value Bigdata shuffle_jars)
-          shuffle_ock_path=$(acquire_value Bigdata shuffle_ock_path)
-          collect_bigdata_components $spark_path
-          collect_bigdata_kal "${algorithms_list[@]}" $algorithms_path "${dataset_list[@]}"
-          collect_bigdata_operator $spark_path $database $omnioperator_dir
-          collect_bigdata_hbase
-          collect_bigdata_tune_up $omniadvisor_dir $mysql_username $mysql_password $mysql_database_name
-          collect_bigdata_omnimv "$omnimv_dir"
-          collect_bigdata_omni_push_down "$omnidata_launcher_server" "$omnidata_launcher" "$push_down_jars" "$push_down_conf" "$spark_path" "$database" "$omnidata_install_path" "$zookeeper_address" "$zookeeper_path"
-          collect_bigdata_omni_shuffle "$spark_path" "$shuffle_jars" "$database" "$shuffle_ock_path"
-          echo "Bigdata collect msg Done..."
-      elif [ $per_project = "Virtual" ];
-      then
-        echo "start collect Virtual msg..."
-        collect_virtual_host
-        server_name=$(acquire_value Virtual server_name)
-        network=$(acquire_value Virtual network)
-        flavor=$(acquire_value Virtual flavor)
-        volume=$(acquire_value Virtual volume)
-        availability_zone=$(acquire_value Virtual availability_zone)
-        collect_virtual_dpu $server_name $network $flavor $volume $availability_zone
-        vm_ip=$(acquire_value Virtual vm_ip)
-        vm_user=$(acquire_value Virtual vm_user)
-        vm_password=$(acquire_value Virtual vm_password)
-        vm_ceph_disk_name=$(acquire_value Virtual vm_ceph_disk_name)
-        vm_name=$(acquire_value Virtual vm_name)
-        collect_virtual_ceph "$vm_ip" "$vm_user" "$vm_password" "$vm_ceph_disk_name" "$vm_name"
-        collect_virtual_ovs_xpf
-        echo "Virtual collect msg Done..."
-      elif [ $per_project = "HPC" ];
-      then
-        echo "start collect HPC msg..."
-        acc_lib=$(acquire_value HPC acc_lib)
-        sme=$(acquire_value HPC sme)
-        sve_source_code=$(acquire_value HPC sve_source_code)
-        collect_hpc_acceleration_library $acc_lib
-        collect_sme_acceleration_library $sme
-        collect_sve_source_code $sve_source_code
-        echo "HPC collect msg Done..."
-		fi
-    done
-}
-
-if [ -e $config_file ]; then
-  customer_information=$(acquire_value Global information)
-  check_customer_info $customer_information
-else
-  echo "config.ini not exist"
-  exit 1
-fi
-main
-tar_log_file $customer_information
+# **鲲鹏使能套件BoostKit验收工具使用说明**
 
+## 1. **采集工具**
 
+### **1.1采集工具能力说明**
 
 
 
+    用于一键收集鲲鹏使能套件BoostKit 特性使能情况信息，以及系统信息，生成统一压缩包（压缩包包含客户id标识信息以及打包时间信息）。 压缩包用于后续分析出具验收报告
 
+系统信息收集包括：操作系统版本信息、内核版本、鲲鹏服务器的机型
 
+软件信息收集包括：BoostKit 下八个解决方案特性是否生效的关键日志信息。 对于未使能的特性，采集过程中会有报错，是正常现象。
 
+- **注意**：只需修改要采集的特性相关的配置，其余配置保持不变即可
+- **注意**：采集过程中会尝试采集对应解决方案下的所有特性，因此对未使能特性的采集出现报错是正常现象，不影响最终结果
 
 
+### **1.2采集工具配置文件说明**
 
+**文件名称**： config.ini
+
+**位置**: 和采集脚本同级目录
+
+**功能**: 用于控制收集是否采集解决方案特性信息以及 必要用户信息输入
+
+
+
+#### **1.2.1大数据配置文件说明**
+
+
+
+![bigdata](./BoostKit_pic/bigdata.png)
+
+> check=False
+
+check 默认为False, 置为True 则开启大数据相关特性使能信息收集功能
+
+ 
+
+> algorithms_path=/home/KAL_TEST_DIR
+
+机器学习和图分析算法加速库安装路径，默认为/home/KAL_TEST_DIR
+
+
+
+> algorithms_name=algorithms_name1  algorithms_name2  algorithms_name3
+
+在$KAL_TEST_DIR/bin/ml/ or $KAL_TEST_DIR/bin/graph/ 目录下有对应 算法名_run.sh 脚本
+
+用户自获取 算法名成填入algorithms_name 对应行，多个算法空格隔开，至少选择四种不同的算法
+
+机器学习和图分析算法加速库的算法名列表，默认为algorithms_name1  algorithms_name2  algorithms_name3
+
+
+
+> dataset_list=dataset1 dataset2 dataset3
+
+机器学习和图分析算法加速库的数据集列表，默认为dataset1 dataset2 dataset3
+
+
+
+> spark_path=/home/
+
+spark的安装路径，默认为/home/
+
+
+
+> database=tpcds_bin_partitioned_orc_1000
+
+所创建对应数据库的名称，根据用户所创建的数据库名称填写，默认为tpcds_bin_partitioned_orc_1000
+
+
+
+> omnioperator_dir=/opt/omni-operator
+
+算子加速的安装路径，默认为/opt/omni-operator
+
+
+
+> omniadvisor_dir=/home
+
+参数调优的安装路径，默认为/home
+
+
+
+> mysql_username=root
+
+可以启动数据库服务的用户名，默认是root用户
+
+
+
+> mysql_password=12345
+
+登录数据库的密码，默认为12345
+
+
+
+> mysql_database_name=xxxxx
+
+所创建对应数据库的名称，根据用户所创建的数据库名称填写
+
+> omnimv_dir=/omnimv
+
+omnimv 目录路径, 用于物化视图特性验证
+
+> omnidata_launcher_server=
+
+launcher 所在服务器的名称 (需可直接ssh无密码访问, 不填则默认在当前服务器上)
+
+> omnidata_launcher=/home/omm/omnidata-install/omnidata/bin/launcher
+
+launcher 二进制路径，用于算子下推特性验证
+
+> omnidata_install_path=/home/omm/omnidata-install
+
+omnidata 安装目录，用于算子下推特性验证
+
+> push_down_jars=/usr/local/spark-plugin-jar/*
+
+算子下推相关jar包路径，用于算子下推特性验证
+
+> push_down_conf=spark.executor.extraClassPath=./*
+
+配置spark参数，用于算子下推特性验证
+
+> zookeeper_address=agent1:2181,agent2:2181,agent3:2181
+
+连接 zookeeper 地址，用于算子下推特性验证
+
+> zookeeper_path=/sdi/status
+
+存放下推资源信息的目录，用于算子下推特性验证
+
+> shuffle_jars=/home/ockadmin/opt/ock/jars/*
+
+shuffle加速相关jar包路径，用于shuffle加速特性验证
+
+> shuffle_ock_path=/home/ockadmin/opt/ock
+
+shuffle加速 ock 安装路径，用于shuffle加速特性验证
+
+#### **1.2.2分布式存储配置文件说明**
+
+![bigdata](./BoostKit_pic/storage.png)
+
+> check=False
+
+check 默认为False, 置为True 则开启分布式存储相关特性使能信息收集功能
+
+ 
+
+> ec_pool_name=ec_pool
+
+注：分布式存储加速算法库特性信息收集 需用户自己先创建 ec_pool， **并回填ec_pool_name至配置文件**
+
+创建流程如下：
+
+ceph osd erasure-code-profile set EC-profile k=4 m=2 plugin=ksal
+
+ceph osd pool create ceph_ecpool 32 32 erasure EC-profile
+
+> ceph_conf=/tmp/ceph.conf
+
+ceph 配置文件路径，用于“压缩算法”特性验收
+
+> storage_maintain_bin=/tmp/maintain
+
+用到存储维护工具库特性的二进制路径
+
+> rocksdb_bin=/tmp/rock.bin
+
+用到Rocksdb元数据加速特性的二进制路径
+
+> ucache_bin=/tmp/ucache.bin
+
+用到Ucache智能读缓存特性的二进制路径
+
+> non_ceph_bin=/tmp/non_ceph.bin
+
+非ceph场景下的软件二进制路径，用于“存储加速算法库”特性验收
+
+> non_ceph_pid=38799 
+
+非ceph场景下的软件进程id，用于“存储加速算法库”特性验收
+
+ 
+
+#### **1.2.3数据库配置文件说明**
+
+![bigdata](./BoostKit_pic/database.png)
+
+> check=False
+
+check 默认为False, 置为True 则开启数据库相关特性使能信息收集功能
+
+> use_mysql=1
+
+是否 mysql 场景下验收，填1或0
+
+> other_db_bin=/usr/losql/pgsql
+
+非mysql场景下，需填写数据库二进制路径
+
+> mysql_install_path=/usr/local/mysql
+
+数据库安装路径，默认为/usr/local/mysql
+
+> mysql_username=root
+
+可以启动数据库服务的用户名，默认是root用户
+
+> mysql_password=123456
+
+登录数据库的密码，默认为123456
+
+> mysql_port=3306
+
+数据库端口，默认为3306
+
+> nvme_name=nvme0n1
+
+nvme盘名称，用于验收 ”MySQL NVMe SSD原子写“ 特性
+
+> database_name=xxxx
+
+所创建对应数据库的名称，根据用户所创建的数据库名称填写
+
+> greenplum_username=root
+
+greenplum 用户名，用于验收“KAEzip压缩解压缩优化”特性
+
+> greenplum_port=5432
+
+greenplum 端口，用于验收“KAEzip压缩解压缩优化”特性
+
+> kae_version=
+
+kae 版本, 填写1.0或2.0, 用于验收“KAEzip压缩解压缩优化”特性
+
+> greenplum_kae_sql=
+
+greenplum kae sql 语句，用于验收“KAEzip压缩解压缩优化”特性
+ 
+
+#### **1.2.4 ARM原生配置文件说明**
+
+![bigdata](./BoostKit_pic/arm_native.png)
+
+> check=False
+
+check 默认为False, 置为True 则开启ARM原生特性使能信息收集功能
+
+> kbox_container=kbox_1
+
+> video_container=android_2
+
+> instuction_container=kbox_3
+
+分别为待采集的kbox、视频流、指令流容器名称。要求3个容器均存在，否则会退出脚本。
+
+ 
+
+
+
+#### **1.2.5加速库配置文件说明**
+
+![bigdata](./BoostKit_pic/acc_lib.png)
+
+工具默认支持验收 KAE 特性，配置文件无需修改
+
+> check=False
+
+check 默认为False, 置为True 则开启加速库特性使能信息收集功能
+
+> system_lib=/home/system_bin
+
+引用系统库二进制文件绝对路径
+
+> HMPP_lib=/home/HMPP_bin
+
+引用HMPP库二进制文件绝对路径
+
+> math_lib=/home/math_bin
+
+引用数学库二进制文件绝对路径
+
+> math_jar=/home/math.jar
+
+引用数学库的jar包位置
+
+> math_java=/home/math.class
+
+引用数学库的字节码文件位置
+
+
+#### **1.2.6虚拟化配置文件说明**
+
+![bigdata](./BoostKit_pic/virtual.png)
+
+
+
+注意：
+
+1.OVS流表网卡加速特性需再host测执行，配置文件无需修改
+
+2.虚拟化DPU卸载 特性需要再DPU测执行采集工具， 配置文件无需修改
+
+3.OVS流表归一化 特性验证前需准备环境，让物理机B上的虚拟机持续ping物理机A上的虚拟机，然后在物理机A上运行采集工具
+该特性默认支持验收， 配置文件无需修改
+
+OpenStack 验证需要以下信息
+
+> server_name=vm1
+
+> network=port1_vdpa01
+
+> flavor=4U4G80G
+
+> volume=ceph1_centos2
+
+> availability_zone=nova:dpu01 
+
+> vm_ip=71.14.48.104
+
+虚拟机ip, 用于验收高性能云盘优化特性
+
+> vm_user=root
+
+虚拟机用户名, 用于验收高性能云盘优化特性
+
+> vm_password=Huawei12#$
+
+虚拟机密码, 用于验收高性能云盘优化特性
+
+> vm_ceph_disk_name=vdb
+
+虚拟机使用的高性能云盘名称, 用于验收高性能云盘优化特性
+
+> vm_name=vm1
+
+虚拟机名称, 用于验收高性能云盘优化特性
+
+#### **1.2.7 机密计算配置文件说明**
+
+![bigdata](./BoostKit_pic/virt.png)
+
+> check=False
+
+check 默认为False, 置为True 则开启数据库相关特性使能信息收集功能
+
+ 
+
+> cvm_name
+
+机密虚机名称,默认为cvm1
+
+> cvm_username
+
+机密虚机的用户名,默认为root
+
+> cvm_password
+
+机密虚机的用户名密码,默认为huawei
+
+ 
+
+#### **1.2.8 HPC配置文件说明**
+
+![bigdata](./BoostKit_pic/hpc.png)
+
+
+
+> check=False
+
+check 默认为False, 置为True 则开启HPC相关特性使能信息收集功能
+
+> acc_lib
+
+引用HPC加速库改造二进制文件绝对路径
+
+> sme
+
+引用HPC SME改造二进制文件绝对路径
+
+> sve_source_code
+
+填写有用到 sve 的源码目录或文件的绝对路径
+
+
+### 1.3 采集工具使用说明
+
+#### 1.3.1 二进制使用
+
+```
+./collect_msg 
+# 同级目录下具有config.ini 配置文件，且已按1.2中对应解决方案完成相关参数配置
+```
+
+#### 1.3.2  shell 脚本使用
+
+```
+bash collect_msg.sh 
+# 同级目录下具有config.ini 配置文件， 且已按1.2中对应解决方案完成相关参数配置
+```
 
-- 
Gitee


From 55dcb7e000e12ac8730a63e0d4ed4eab0ac0fb97 Mon Sep 17 00:00:00 2001
From: ksun <sunkai71@huawei.com>
Date: Fri, 6 Sep 2024 02:57:25 +0000
Subject: [PATCH 3/4] =?UTF-8?q?=E6=81=A2=E5=A4=8D=20tools/collect=5Fmsg.sh?=
 =?UTF-8?q?.?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: ksun <sunkai71@huawei.com>
---
 tools/collect_msg.sh | 1295 +++++++++++++++++++++++++++++-------------
 1 file changed, 901 insertions(+), 394 deletions(-)

diff --git a/tools/collect_msg.sh b/tools/collect_msg.sh
index ed50b75..113d2d8 100644
--- a/tools/collect_msg.sh
+++ b/tools/collect_msg.sh
@@ -1,406 +1,913 @@
-# **鲲鹏使能套件BoostKit验收工具使用说明**
+#!/bin/bash
+current_path=$(pwd)
+config_file=$current_path/config.ini
+log_path=$current_path/log
+default_project="Bigdata Database Storage Arm Virt Acclib Virtual HPC"
+
+
+
+
+
+#####################根据section以及key值获取对应value############
+acquire_value(){
+    project=$1
+    key=$2
+    opt="{sub(/$key=/,\"\")}1"
+    grep $project -A 100  $config_file |grep -m 1 "$key="|awk $opt
+}
+
+
+######################获取配置文件中选择校验的解决方案###########
+acquire_select_project(){
+    all_name=""
+	for per_project in $default_project
+	do
+		status=$(acquire_value $per_project check)
+		if [[ $status = True ]]; then
+			all_name="$all_name $per_project"
+        fi
+	done
+	echo $all_name
+}
+
+
+check_customer_info(){
+  customer_information=$1
+  if [  -z "$customer_information" ];
+  then
+    echo "请您在config.ini Global字段 填写唯一个人标识 eg: xxx有限公司"
+    exit 1
+  fi
+
+  if [[ "$customer_information"x =~ "xxx有限公司" ]];
+  then
+    echo "请您在config.ini Global字段 修改 xxx有限公司为具体公司名称以供标识"
+    exit 1
+  fi
+}
+
+
+####################打包日志文件############################
+tar_log_file(){
+  customer_information=$1
+  datatime=$(date '+%Y%m%d%H%M')
+
+  if test -d $log_path;
+  then
+      echo "customer_information: ${customer_information}_isv_msg_${datatime}.tar.gz" >> $log_path/os_msg.log
+      tar zcvf ${customer_information}_isv_msg_${datatime}.tar.gz -C $log_path .
+  else
+      echo "$log_path logpath abnormality, please check"
+  fi
+}
+
+
+###################arm原生特性信息收集#################
+collect_arm_native(){
+     kbox_container=$1
+     video_container=$2
+     instruction_container=$3
+     # check tested container whether exist
+     containers=($1 $2 $3)
+     for i in ${containers[@]};do
+	     docker ps -a | grep -wq $i || { echo "the $i container doesn't found,please check!"; exit 1; }
+     done
+     # kbox基础云手机
+     rm -f $log_path/arm_native.log
+
+     keyword=(gralloc.kbox.so audio.primary.kbox.so gps.kbox.so sensors.kbox.so libmedia_omxcore.so libstagefrighthw.so vinput hwcomposer.kbox.so)
+     docker exec -it $kbox_container lsof > $log_path/arm_native_raw.log
+     for i in "${keyword[@]}";do
+	     grep -F "${i}" $log_path/arm_native_raw.log >> $log_path/arm_native.log
+     done
+     rm -f $log_path/arm_native_raw.log
+
+     docker exec -it $kbox_container cat /proc/sys/fs/binfmt_misc/ubt_a32a64 >> $log_path/arm_native.log
+     # 视频流
+     docker exec -it $video_container lsof | grep VmiInputFlinger >> $log_path/arm_native.log
+     # 指令流
+     docker exec -it $instruction_container ps -ef | grep -F "VmiAgent instruction" >> $log_path/arm_native.log
+}
+
+
+#################虚拟化特性信息收集##################
+collect_virtual_host(){
+    sudo systemctl status waasagent.service |grep "Active" > $log_path/virtual_sense.log
+    waasctl --version >> $log_path/virtual_sense.log
+
+    ovs_appctl_res=$(ovs-appctl --version 2>&1)
+
+    if [[ $ovs_appctl_res =~ "command not found" ]];
+    then
+        echo "ovs-appctl: command not found" > $log_path/virtual_dpu_flow.log
+    else
+        echo "ovs-appctl version: $ovs_appctl_res" > $log_path/virtual_dpu_flow.log
+		script -a -c 'ovs-appctl hwoff/dump-hwoff-flows' $log_path/virtual_dpu_flow.log
+    fi
+}
+
+
+collect_virtual_dpu(){
+    server_name=$1
+    network=$2
+    flavor=$3
+    volume=$4
+	availability_zone=$5
+
+    # 需要再DPU测执行
+    dpak_ovs_ctl_res=$(dpak-ovs-ctl -h 2>&1)
+    if [[ $dpak_ovs_ctl_res =~ "command not found" ]];
+    then
+        echo "请确定已在DPU测执行该工具"
+        echo "dpak_ovs_ctl: command not found" > $log_path/virtual_dpu.log
+    else
+        echo "dpak_ovs_ctl version: $dpak_ovs_ctl_res" > $log_path/virtual_dpu.log
+		script -a -c 'dpak-ovs-ctl hwoff/dump-hwoff-flows' $log_path/virtual_dpu.log
+    fi
+
+	  /usr/libexec/spdk/scripts/hw_dpu_rpc.py get_version >> $log_path/virtual_dpu.log 2>&1
+    /usr/libexec/spdk/scripts/hw_dpu_rpc.py get_controllers >> $log_path/virtual_dpu.log 2>&1
+
+    # 创建虚机
+    openstack_res=$(openstack --version 2>&1)
+
+    if [[ $openstack_res =~ "command not found" ]];
+    then
+        echo "请确定已在DPU测执行该工具"
+        echo "openstack: command not found" >> $log_path/virtual_dpu.log
+    else
+        echo "openstack version: $openstack_res" >> $log_path/virtual_dpu.log
+        openstack server create $server_name --network $network --flavor $flavor --volume $volume --availability-zone $availability_zone >> $log_path/virtual_dpu.log
+		echo "等待虚机创建完成"
+        sleep 120
+        echo "server_name: $server_name" >> $log_path/virtual_dpu.log
+        openstack server list >> $log_path/virtual_dpu.log
+    fi
+}
+
+
+collect_virtual_ceph(){
+  vm_ip=$1
+  vm_user=$2
+  vm_password=$3
+  vm_ceph_disk_name=$4
+  vm_name=$5
+  set -x
+  sshpass -p "$vm_password" ssh "$vm_user"@"$vm_ip" ls -la /sys/block/ | grep $vm_ceph_disk_name | tail -n 1 > $log_path/virtual_ceph_disk.log
+  virsh dumpxml $vm_name > $log_path/virtual_ceph_vm_xml.log
+  rpc vhost_get_controllers > $log_path/virtual_ceph_vm_controllers.log
+  rpc bdev_get_bdevs > $log_path/virtual_ceph_bdev.log
+}
+
+
+collect_virtual_ovs_xpf(){
+  ovs-appctl hwoff/dump-hwoff-flows > $log_path/virtual_ovs_xpf.log
+  echo $? >> $log_path/virtual_ovs_xpf.log
+}
+
+
+################数据库特性信息收集##################
+collect_database(){
+   mysql_install_path=$1
+   mysql_username=$2
+   mysql_password=$3
+   mysql_port=$4
+   database_name=$5
+   nvme_name=$6
+   plugin_path=$1/lib/plugin
+   timeout=60
+   $mysql_install_path/bin/mysqld_safe --defaults-file=/etc/my.cnf &
+   # 循环判断进程是否启动
+   for ((i=0; i<=$timeout; i++)); do
+     if ps -ef | grep -v grep | grep "mysql" > /dev/null; then
+       echo "Process mysql started."
+       # 执行下一步操作
+       sleep 5
+       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "select * from INFORMATION_SCHEMA.plugins where PLUGIN_NAME like 'thread_pool%'" > $log_path/database_mysql_thread_pool.log
+       echo thread_pool: $(ls $plugin_path |grep thread_pool.so) >> $log_path/database_mysql_thread_pool.log
+       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "show variables like 'thread_pool%'" > $log_path/database_mysql_thread_pool_variable.log
+       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "select * from INFORMATION_SCHEMA.plugins where PLUGIN_NAME like 'kovae%'" >> $log_path/database_mysql.log
+       echo kovae_path: $(ls $plugin_path |grep ha_kovae.so) >>  $log_path/database_mysql.log
+       readelf -a $mysql_install_path/bin/mysqld|grep bolt >> $log_path/database_mysql.log
+       echo no_lock: $(objdump -d $mysql_install_path/bin/mysqld|grep -c row_vers_build_for_semi_consistent_readP5trx_t) >> $log_path/database_mysql.log
+       objdump -d $mysql_install_path/bin/mysqld |grep crc32cb >> $log_path/database_mysql.log
+       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "show variables like '%paralle%'" >> $log_path/database_mysql.log
+       nm $mysql_install_path/bin/mysqld | grep -c Page_shards >> $log_path/database_mysql_page_shards.log
+       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "show variables like 'sched_affinity%'" >> $log_path/database_mysql.log
+       hioadm atomicwrite -d $nvme_name > $log_path/database_mysql_nvme.log
+       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "show variables like '%flush_method%'" >> $log_path/database_mysql_nvme.log
+       $mysql_install_path/bin/mysql -P $mysql_port -u $mysql_username -p$mysql_password -D $database_name -h127.0.0.1 -e "show variables like '%doublewrite%'" >> $log_path/database_mysql_nvme.log
+       gazellectl lstack show 1 -c | grep ":$mysql_port" > $log_path/database_mysql_gazelle.log
+       pkill -9 mysql
+       break
+     fi
+     sleep 1
+     if [ $timeout -eq $i ];then
+       echo "Timeout error: mysql process not started in $timeout seconds.i"
+       exit 1
+     fi
+   done
+}
+
+
+collect_database_other_db(){
+  other_db_bin=$1
+  greenplum_username=$2
+  greenplum_port=$3
+  kae_version=$4
+  greenplum_kae_sql=$5
+  readelf -a $other_other_db_bin | grep bolt > $log_path/database_other_db.log
+  objdump -d $other_other_db_bin | grep crc32cb >> $log_path/database_other_db.log
+  if [ "$kae_version" == "1.0" ]; then
+    nohup timout 20 watch -gt -n 0.2 cat /sys/class/uacce/hisi_zip*/attrs/available_instances > $log_path/database_greenplum_kae.log &
+  else
+    nohup timeout 20 watch -gt -n 0.2 cat /sys/class/uacce/hisi_zip*/available_instances > $log_path/database_greenplum_kae.log &
+  fi
+  psql -h 127.0.0.1 -p $greenplum_port -U $greenplum_username -c "$greenplum_kae_sql"
+}
+
+
+####################机密计算特性信息收集################
+collect_virtcca_msg(){
+		cvm_name=$1
+	username=$2
+	passwd=$3
+	xml_path=/tmp/temp.xml
+	virsh list --all|grep -q $cvm_name
+	if [ $? -ne 0 ]; then
+    		echo "错误：虚拟机 $cvm_name 不存在"
+    		return 0
+	fi
+	vm_status=$(virsh domstate "$cvm_name")
+
+	if [ "$vm_status" == "shut off" ]; then
+    		echo "虚拟机 $cvm_name 处于 shut off 状态，正在启动..."
+    		virsh start "$cvm_name"
+    		echo "虚拟机 $cvm_name 启动完成"
+	elif [ "$vm_status" == "running" ]; then
+    		echo "虚拟机 $cvm_name 处于 running 状态，无需操作"
+	else
+    		echo "错误：无法确定虚拟机 $cvm_name 的状态"
+   	        return 0
+	fi
+
+	virsh dumpxml $cvm_name > $xml_path
+	ret=$(grep -i "type='cvm'" $xml_path)
+	echo "$ret" > $log_path/virtcca_status.log
+	expect << EOF >> $log_path/virtcca_status.log
+        spawn virsh console $cvm_name
+        expect "Escape character is \\^]"
+        send "\r"
+        expect "login:"
+        send "$username\r"
+        expect "Password:"
+        send "$passwd\r"
+	expect "# "
+	send "ls -l /\r"
+	expect "# "
+	send "exit\r"
+	expect eof
+EOF
+}
+
+
+collect_ccos_msg(){
+    /vendor/bin/tee-check > $log_path/virtccos_itrustee.log
+    tlogcat -f &
+    sleep 3s
+    cat /var/log/tee/teeOS_log-0  | grep UUID >> $log_path/virtccos_itrustee.log
+    ps aux | grep tlogcat | awk '{print $2}' | xargs kill
+}
+
+
+#################加速库特性信息收集##################
+collect_acceleration_library(){
+    system_lib=$1
+    hmpp_lib=$2
+    math_lib=$3
+    math_jar=$4
+    math_java=$5
+    openssl speed -elapsed -engine kae rsa2048  > $log_path/acceleration_library.log 2>&1
+    ldd $1 >> $log_path/acceleration_library.log
+    ldd $2 >> $log_path/acceleration_library.log
+    ldd $3 >> $log_path/acceleration_library.log
+    jar -tf $4 >> $log_path/acceleration_library_kml_java.log
+    javap -v $5 >> $log_path/acceleration_library_kml_java.log
+}
+
+
+###############分布式存储特性信息收集###############
+# $1 ec_pool 名字
+collect_storage_acc(){
+    ec_pool=$1
+    ceph_conf=$2
+    storage_maintain_bin=$3
+    rocksdb_bin=$4
+    ucache_bin=$5
+    non_ceph_bin=$6
+    non_ceph_pid=$7
+    # 存储加速库
+    ldd /usr/bin/ceph-osd > $log_path/storage_acc.log
+    bcache_dev=$(ls /sys/class/block|grep -m 1 bcache)
+    # 如果没有课增加异常判断
+    ls -l /sys/class/block/$bcache_dev/bcache/cache/internal/traffic_policy_start >> $log_path/storage_acc.log
+
+    pool_list=$(sudo rados lspools |grep -wx $ec_pool)
+    if [[ $pool_list =~ $ec_pool ]];
+    then
+	      echo "ec_pool created" >> $log_path/storage_acc.log
+	      pid_num=$(ps -ef|grep  osd|grep -v grep|head -n 1|awk '{print $2}')
+	      sudo cat /proc/$pid_num/smaps |grep ksal >> $log_path/storage_acc.log
+    else
+	      echo "ec_pool not exist" >> $log_path/storage_acc.log
+    fi
+
+    systemctl status ceph-boost.service > $log_path/storage_io.log
+    if ceph osd pool set vdbench compression_algorithm glz; then
+      \cp "$ceph_conf" "$ceph_conf".bak
+      sed -i '/^compressor_glz_level/d' "$ceph_conf"
+      echo "compressor_glz_level = 1" >> "$ceph_conf"
+      systemctl restart ceph.target
+      systemctl status ceph.target > $log_path/storage_comporess.log
+      \cp "$ceph_conf".bak "$ceph_conf"
+    fi
+    ldd $storage_maintain_bin > $log_path/storage_maintain_tool.log
+    lib_rocksdb=$(ldd $rocksdb_bin | grep librocksdb | awk '{print $3}')
+    ldd $lib_rocksdb > $log_path/storage_rocksdb.log
+    ldd $ucache_bin > $log_path/storage_ucache.log
+
+    if ldd $non_ceph_bin | grep ksal; then
+      timeout 20 perf top -p $non_ceph_pid > $log_path/storage_non_ceph_perf_top.log
+    fi
+}
+
+
+###############大数据特性信息收集##################
+collect_bigdata_kal(){
+  algotithm_list=$1
+  algotithm_path=$2
+  dataset_list=$3
+
+  read -r -a  algotithm_arry <<< "$algotithm_list"
+  read -r -a  dataset_arry <<< "$dataset_list"
+
+  cd $algotithm_path
+  index=0
+  for per_alg in ${algotithm_list[*]}
+  do
+      # "Usage: <dataset name> <is raw> <is check>","1st argument: name of dataset: cit_patents, enwiki_2018, uk_2002","2nd argument: optimization algorithm or raw: no/yes","3rd argument: verify result: no/yes"
+      if [ "$per_alg" == "betweenness" ] || [ "$per_alg" == "node2vec" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage:<dataset name> <is raw>","1st argument: name of dataset: cit_patents,enwiki_2018,arabic_2005,graph500_22,graph500_23,graph500_25","2nd argument: optimization algorithm or raw: no/yes"
+      if [ "$per_alg" == "bfs" ] || [ "$per_alg" == "cc" ] || [ "$per_alg" == "deepwalk" ] || [ "$per_alg" == "diameter" ] || [ "$per_alg" == "ecc" ] || [ "$per_alg" == "fraudar" ] || [ "$per_alg" == "katz" ] || [ "$per_alg" == "kcore" ] || [ "$per_alg" == "ktruss" ] || [ "$per_alg" == "louvain" ] || [ "$per_alg" == "modularity" ] || [ "$per_alg" == "mst" ] || [ "$per_alg" == "scc" ] || [ "$per_alg" == "slpa" ] || [ "$per_alg" == "tpr" ] || [ "$per_alg" == "trussdecomposition" ] || [ "$per_alg" == "wlpa" ] || [ "$per_alg" == "wmssp" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage:<dataset name>","dataset name: simulate1,simulate2,usaRoad"
+      if [ "$per_alg" == "cd" ] || [ "$per_alg" == "inccc" ] || [ "$per_alg" == "mce" ] || [ "$per_alg" == "wce" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <weight or not> <isRaw>","1st argument: name of dataset: name of dataset: cit_patents,uk_2002","2nd argument: weight or not: e.g. weighted,unweighted","3rd argument: verify result: no/yes"
+      if [ "$per_alg" == "closeness" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} weight no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <api name> <weight or not> <isRaw>","1st argument: name of dataset: name of dataset: cit_patents,uk_2002,arabic_2005,graph500_22,graph500_23,graph500_24,graph500_25"
+      # "2nd argument: name of api: lcc,avgcc,globalcc","3nd argument: weight or not: weighted,unweighted","4th argument: optimization algorithm or raw: no/yes"
+      if [ "$per_alg" == "clusteringcoefficient" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} lcc weighted no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <api name> <isRaw>","1st argument: name of dataset: it_2004,twitter7,uk_2007_05,mycielskian20,gap_kron,com_friendster"
+      # "2nd argument: name of api: degrees,inDegrees,outDegrees","3rd argument: optimization algorithm or raw: no/yes"
+      if [ "$per_alg" == "degree" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} degrees no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <rate> <batch> <isRaw>","1st argument: name of dataset: twitter_2010","2nd argument: rate: e.g. 0.001,0.01,0.05"
+      # "3nd argument: batch: e.g. 1,2,3,4,5","4th argument: optimization algorithm or raw: no/yes"
+      if [ "$per_alg" == "incpr" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} 0.001 1 no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <queryGraph name> <identical or not>","1st argument: name of dataset: name of dataset: graph500_21,com_orkut"
+      # "2nd argument: name of queryGraph: for Identical: 4dgn/4sqr/6star; for unIdentical: 4dgn/4sqr/4clique/5clique/6clique","3rd argument: match mode:Identical,unIdentical"
+      if [ "$per_alg" == "incsgm" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} 4dgn Identical > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <api name> <isRaw>","1st argument: name of dataset: graph500_22,graph500_24,graph500_25","2nd argument: api: run,runConvergence","3rd argument: optimization algorithm or raw: no/yes"
+      if [ "$per_alg" == "lpa" ] || [ "$per_alg" == "pr" ] || [ "$per_alg" == "tc" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} run no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <source number> <isRaw>","1st argument: name of dataset: soc_liveJournal,uk_2002,arabic_2005","2nd argument: source number: 5/50","3rd argument: optimization algorithm or raw: no/yes"
+      if [ "$per_alg" == "mssp" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} 5 no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <isRaw>","1st argument: name of dataset: epinions, graph500_23_weight, graph500_25_weight","2nd argument: anomaly_type: 0/1","3rd argument: optimization algorithm or raw: no/yes"
+      if [ "$per_alg" == "oddball" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} 0 no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <api name> <isRaw> <sourceCnt>","1st argument: name of dataset: cit_patents,uk_2002,arabic_2005","2nd argument: name of api: fixMS,fixSS,conSS"
+      # "3rd argument: optimization algorithm or raw: no/yes","4th argument: sourceCnt or null: 1,5,10,50,100"
+      if [ "$per_alg" == "ppr" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} fixMS no 1 > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <queryGraph name> <identical or not> <isRaw>","1st argument: name of dataset: name of dataset: graph500_19,liveJournal,com_orkut"
+      # "2nd argument: name of queryGraph: for Identical: 4dgn/4sqr/5tree/6star; for unIdentical: 4dgn/4clique/5clique/6clique","3rd argument: match mode:Identical,unIdentical","4th argument: optimization algorithm or raw: no/yes"
+      if [ "$per_alg" == "sgm" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} 4dgn Identical no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <api name> <seeds count>","1st argument: name of dataset: cit_patents,uk_2002,arabic_2005","2nd argument: name of api: run,runUntilConvergence","3nd argument: seeds count: 100,500,1000"
+      if [ "$per_alg" == "tr" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} run 100 > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <api name> <isRaw>","1st argument: name of dataset: cage14, GAP_road, GAP_twitter","2nd argument: name of api: static, convergence","3rd argument: optimization algorithm or raw: no, yes"
+      if [ "$per_alg" == "wpr" ];
+      then
+          bash $algotithm_path/bin/graph/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} static no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <data structure> <dataset name> <api name> <isRaw> <isCheck>","1st argument: type of data structure: [dataframe/rdd]","2nd argument: name of dataset: e.g. als/alsbs/alsh"
+      # "3rd argument: name of API: e.g. fit/fit1/fit2/fit3; for rdd: train","4th argument: optimization algorithm or raw: [no/yes]","5th argument: Whether to Compare Results [no/yes]"
+      if [ "$per_alg" == "als" ] || [ "$per_alg" == "kmeans" ] || [ "$per_alg" == "lda" ] || [ "$per_alg" == "pca" ];
+      then
+          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh dataframe ${dataset_arry[$index]} fit no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <isRaw> <isCheck>","1st argument: name of dataset: e.g. CP10M1K/CP2M5K/CP1M10K","2nd argument: optimization algorithm or raw: [no/yes]","3rd argument: Whether to Compare Results [no/yes]"
+      if [ "$per_alg" == "bo" ] || [ "$per_alg" == "cov" ] || [ "$per_alg" == "crf" ] || [ "$per_alg" == "encoder" ] || [ "$per_alg" == "fpg" ] || [ "$per_alg" == "hdb" ] || [ "$per_alg" == "idf" ] || [ "$per_alg" == "if" ] || [ "$per_alg" == "nmf" ] || [ "$per_alg" == "ps" ] || [ "$per_alg" == "simrank" ] || [ "$per_alg" == "svd" ] || [ "$per_alg" == "te" ];
+      then
+          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <isRaw>","1st argument: name of dataset: e.g. bremenSmall/farm/house","2nd argument: optimization algorithm or raw: [no/yes]"
+      if [ "$per_alg" == "dbscan" ] || [ "$per_alg" == "knn" ];
+      then
+          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <algorithm type> <data structure> <dataset name> <api name> <isRaw> <ifCheck>","1st argument: type of algorithm: [classification/regression]","2nd argument: type of data structure: [dataframe/rdd]"
+      # "3rd argument: name of dataset: [epsilon/higgs/mnist8m]","4th argument: name of API: [for dataframe: fit/fit1/fit2/fit3; for rdd: trainClassifier/trainRegressor]","5th argument: optimization algorithm or raw: [no/yes]"
+      # "6th argument: Whether to Compare Results [no/yes]"
+      if [ "$per_alg" == "dt" ] || [ "$per_alg" == "gbdt" ] || [ "$per_alg" == "rf" ];
+      then
+          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh classification dataframe ${dataset_arry[$index]} fit no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <api name> <save or verify> <isRaw>","1st argument: name of dataset: higgs/mnist8m","2nd argument: name of API: fit/fit1/fit2/fit3"
+      # "3rd argument: save or verify result: save/verify","4th argument: optimization algorithm or raw: no/yes"
+      if [ "$per_alg" == "dtb" ];
+      then
+          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} fit verify no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <algorithm type> <data structure> <dataset name> <api name> <isRaw> <isCheck>","1st argument: type of algorithm: [classification/regression]"
+      # "2nd argument: name of dataset: [higgs/avazu]","3rd argument: name of API: [fit]"
+      # "4th argument: optimization algorithm or raw: [no/yes]","5th argument: Whether to Compare Results [no/yes]"
+      if [ "$per_alg" == "fm" ];
+      then
+          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh classification ${dataset_arry[$index]} fit no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <algorithm type> <dataset name> <isRaw> <isCheck>","1st argument: type of algorithm: [classification/regression]","2nd argument: name of dataset:mnist8m, higgs "
+      # "3rd argument: optimization algorithm or raw: [no/yes]","4th argument: Whether to Compare Results [no/yes]"
+      if [ "$per_alg" == "lgbm" ];
+      then
+          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh classification ${dataset_arry[$index]} no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <api name> <isRaw> <isCheck>","1st argument: name of dataset: e.g. mnist8m/Twitter/rcv"
+      # "2nd argument: name of API: e.g. fit/fit1/fit2/fit3","3th argument: optimization algorithm or raw: [no/yes]","4th argument: Whether to Compare Results [no/yes]"
+      if [ "$per_alg" == "linR" ] || [ "$per_alg" == "logR" ] || [ "$per_alg" == "spca" ] || [ "$per_alg" == "svm" ];
+      then
+          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} fit no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <data structure> <dataset name> <isRaw> <isCheck>","1st argument: type of data structure: [dataframe/rdd]","2nd argument: name of dataset: e.g. CP10M1K/CP2M5K/CP1M10K"
+      # "3nd argument: optimization algorithm or raw: [no/yes]","4rd argument: Whether to Compare Results [no/yes]"
+      if [ "$per_alg" == "pearson" ] || [ "$per_alg" == "spearman" ];
+      then
+          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh dataframe ${dataset_arry[$index]} no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <api name> <isRaw>","1st argument: name of dataset: cate/node/item/taobao","2nd argument: name of API: fit/fit1/fit2/fit3","3rd argument:optimization algorithm or raw: no/yes"
+      if [ "$per_alg" == "word2vec" ];
+      then
+          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} fit no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      # "Usage: <dataset name> <algorithm type> <isRaw> <isCheck>","1rd argument: name of dataset: e.g. higgs/mnist8m","2st argument: type of algorithm: [classification/regression]"
+      # "3th argument: optimization algorithm or raw: [no/yes]","4th argument: Whether to Compare Results [no/yes]"
+      if [ "$per_alg" == "xgbt" ];
+      then
+          bash $algotithm_path/bin/ml/${algotithm_arry[$index]}_run.sh ${dataset_arry[$index]} classification no no > $log_path/bigdata_kal_${algotithm_arry[$index]}_${dataset_arry[$index]}.log 2>&1
+      fi
+      index=`expr $index + 1`
+  done
+
+}
+
+
+collect_bigdata_operator(){
+        # 日志记录位置 log_path/bigdata_operator.log
+	spark_path=$1
+	database=$2
+    omnioperator_dir=$3
+	if [ -e $spark_path ] && [ -e $omnioperator_dir ];
+	then
+        spark_version=`awk '{print $2}' $spark_path/RELEASE | head -n 1`
+        omnioperator_version=`cat $omnioperator_dir/version.txt | grep 'Component Version' | awk -F ": " '{print $2}'`
+        echo "spark version:$spark_version omnioperator version:$omnioperator_version" >$log_path/bigdata_operator.log 2>&1
+        spark_omni_func=(
+        --deploy-mode client
+        --driver-cores 5
+        --driver-memory 5g
+        --num-executors 6
+        --executor-cores 2
+        --executor-memory 6g
+        --master yarn
+        --conf spark.memory.offHeap.enabled=true
+        --conf spark.memory.offHeap.size=18g
+        --conf spark.task.cpus=1
+        --conf spark.driver.extraClassPath=${omnioperator_dir}/lib/boostkit-omniop-spark-${spark_version}-${omnioperator_version}-aarch64.jar:${omnioperator_dir}/lib/boostkit-omniop-bindings-${omnioperator_version}-aarch64.jar:${omnioperator_dir}/lib/dependencies/*
+        --conf spark.executor.extraClassPath=${omnioperator_dir}/lib/boostkit-omniop-spark-${spark_version}-${omnioperator_version}-aarch64.jar:${omnioperator_dir}/lib/boostkit-omniop-bindings-${omnioperator_version}-aarch64.jar:${omnioperator_dir}/lib/dependencies/*
+        --driver-java-options -Djava.library.path=${omnioperator_dir}/lib
+        --conf spark.sql.codegen.wholeStage=false
+        --conf spark.executorEnv.LD_LIBRARY_PATH=${omnioperator_dir}/lib
+        --conf spark.executorEnv.OMNI_HOME=${omnioperator_dir}/
+        --conf spark.driverEnv.LD_LIBRARY_PATH=${omnioperator_dir}/lib
+        --conf spark.driverEnv.OMNI_HOME=${omnioperator_dir}/
+        --conf spark.executor.extraLibraryPath=${omnioperator_dir}/lib
+        --conf spark.driverEnv.LD_PRELOAD=${omnioperator_dir}/lib/libjemalloc.so.2
+        --conf spark.executorEnv.LD_PRELOAD=${omnioperator_dir}/lib/libjemalloc.so.2
+        --conf spark.sql.extensions=com.huawei.boostkit.spark.ColumnarPlugin
+        --jars ${omnioperator_dir}/lib/boostkit-omniop-spark-${spark_version}-${omnioperator_version}-aarch64.jar
+        --jars ${omnioperator_dir}/lib/boostkit-omniop-bindings-${omnioperator_version}-aarch64.jar
+        --conf spark.sql.orc.impl=native
+        --conf spark.shuffle.manager=org.apache.spark.shuffle.sort.OmniColumnarShuffleManager
+        --conf spark.omni.sql.columnar.fusion=false
+        --conf spark.omni.sql.columnar.sortSpill.enabled=true
+        --conf spark.omni.sql.columnar.sortSpill.rowThreshold=4000000
+        --conf spark.omni.sql.columnar.sortSpill.dirDiskReserveSize=214748364800
+        --conf spark.locality.wait=8
+        --conf spark.sql.autoBroadcastJoinThreshold=10M
+        --conf spark.sql.broadcastTimeout=500
+        --conf spark.sql.cbo.enabled=false
+        --conf spark.default.parallelism=200
+        --conf spark.sql.shuffle.partitions=200
+        --conf spark.executorEnv.MALLCO_CONF=narenas:2
+)
+
+	    spark_conf_path=$1/conf
+        if [ X"${spark_version}" == "X3.1.1" ];then
+            if [ ! -f $spark_conf_path/log4j.properties ];then
+                cp $spark_conf_path/log4j.properties.template $spark_conf_path/log4j.properties
+            fi
+            if ! cat < $spark_conf_path/log4j.properties|grep "^log4j.logger.com.huawei.boostkit.spark=INFO";
+            then
+                    echo "log4j.logger.com.huawei.boostkit.spark=INFO" >> $spark_conf_path/log4j.properties
+            fi
+        elif [ X"${spark_version}" == "X3.3.1" ];then
+            if [ ! -f $spark_conf_path/log4j2.properties ];then
+                cp $spark_conf_path/log4j2.properties.template $spark_conf_path/log4j2.properties
+            fi
+            sed -i "s/^logger.thriftserver.level =.*/logger.thriftserver.level = INFO/" $spark_conf_path/log4j2.properties
+        else
+            echo "Spark ${spark_version} is not supported." >>$log_path/bigdata_operator.log 2>&1
+        fi
+	    $spark_path/bin/spark-sql "${spark_omni_func[@]}" --database $database -e "WITH customer_total_return AS ( SELECT sr_customer_sk AS ctr_customer_sk, sr_store_sk AS ctr_store_sk, sum(sr_return_amt) AS ctr_total_return FROM store_returns, date_dim WHERE sr_returned_date_sk = d_date_sk AND d_year = 2000 GROUP BY sr_customer_sk, sr_store_sk) SELECT c_customer_id FROM customer_total_return ctr1, store, customer WHERE ctr1.ctr_total_return > (SELECT avg(ctr_total_return) * 1.2 FROM customer_total_return ctr2 WHERE ctr1.ctr_store_sk = ctr2.ctr_store_sk) AND s_store_sk = ctr1.ctr_store_sk AND s_state = 'TN' AND ctr1.ctr_customer_sk = c_customer_sk ORDER BY c_customer_id LIMIT 100;" 1>>$log_path/bigdata_operator.log 2>&1
+	else
+	    echo "$spark_path or $omnioperator_dir does not exist" >$log_path/bigdata_operator.log 2>&1
+	fi
+}
+
+
+collect_bigdata_hbase(){
+
+   hbase com.huawei.boostkit.hindex.mapreduce.GlobalTableIndexer -Dtablename.to.index=OnlySingleIndexTable -Dindexspecs.to.addandbuild='osindex=>C0:[F1]'
+   hbase shell << EOF > $log_path/bigdata_hbase.log 2>&1
+   debug
+   scan 'OnlySingleIndexTable',{FILTER=>"(SingleColumnValueFilter('C0', 'F1',=,'binary:bbb')"}
+   exit
+EOF
+}
+
+
+collect_bigdata_tune_up(){
+   omniadvisor_dir=$1
+   mysql_username=$2
+   mysql_password=$3
+   mysql_database=$4
+   if [ -e $omniadvisor_dir/omniadvisor ];
+   then
+       echo "omniadvisor.log" >> $log_path/bigdata_tune_up.log
+   else
+      echo "omniadvisor.log not exist" >> $log_path/bigdata_tune_up.log
+   fi
+
+   mysql -u $mysql_username -p$mysql_password -D $mysql_database  -e "show tables" >> $log_path/bigdata_tune_up.log 2>&1
+
+}
+
+
+collect_bigdata_omnimv(){
+  omnimv_dir=$1
+  hdfs dfs -ls $omnimv_dir > $log_path/bigdata_omnimv.log
+}
+
+
+collect_bigdata_omni_push_down(){
+  omnidata_launcher_server=$1
+  omnidata_launcher=$2
+  push_down_jars=$3
+  push_down_conf=$4
+  spark_path=$5
+  database=$6
+  omnidata_install_path=$7
+  zookeeper_address=$8
+  zookeeper_path=$9
+
+  if [  -z "$omnidata_launcher_server" ]; then
+    sh $omnidata_launcher status > $log_path/bigdata_omni_launcher_status.log
+  else
+    ssh $omnidata_launcher_server sh $omnidata_launcher status > $log_path/bigdata_omni_launcher_status.log
+  fi
+  cat << EOF > /tmp/log4j.properties
+log4j.rootCategory=INFO, FILE
+log4j.appender.console=org.apache.log4j.ConsoleAppender
+log4j.appender.console.target=System.err
+log4j.appender.console.layout=org.apache.log4j.PatternLayout
+log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n
+
+log4j.logger.org.apache.spark.sql.execution=DEBUG
+log4j.logger.org.apache.spark.repl.Main=INFO
+
+log4j.appender.FILE=org.apache.log4j.FileAppender
+log4j.appender.FILE.file=$log_path/bigdata_omni_push_down.log
+log4j.appender.FILE.layout=org.apache.log4j.PatternLayout
+
+log4j.appender.FILE.layout.ConversionPattern=%m%n
+EOF
+  # 这里直接用 operator 的采集 sql
+  $spark_path/bin/spark-sql --driver-class-path "$push_down_jars" --jars "$push_down_jars" \
+  --conf "$push_down_conf" \
+  --conf spark.sql.cbo.enabled=true \
+  --conf spark.sql.cbo.planStats.enabled=true \
+  --conf spark.sql.ndp.enabled=true \
+  --conf spark.sql.ndp.filter.selectivity.enable=true \
+  --conf spark.sql.ndp.filter.selectivity=0.5 \
+  --conf spark.sql.ndp.alive.omnidata=3 \
+  --conf spark.sql.ndp.table.size.threshold=10 \
+  --conf spark.sql.ndp.zookeeper.address=$zookeeper_address \
+  --conf spark.sql.ndp.zookeeper.path=$zookeeper_path \
+  --conf spark.sql.ndp.zookeeper.timeout=15000 \
+  --conf spark.driver.extraLibraryPath=$omnidata_install_path/haf-host/lib \
+  --conf spark.executor.extraLibraryPath=$omnidata_install_path/haf-host/lib \
+  --conf spark.executorEnv.HAF_CONFIG_PATH=$omnidata_install_path/haf-host/etc/ \
+  --name tpcds_test.sql --driver-memory 50G --driver-java-options -Dlog4j.configuration=file:/tmp/log4j.properties \
+  --executor-memory 32G --num-executors 30 --executor-cores 18 --database $database \
+  -e "WITH customer_total_return AS ( SELECT sr_customer_sk AS ctr_customer_sk, sr_store_sk AS ctr_store_sk, sum(sr_return_amt) AS ctr_total_return FROM store_returns, date_dim WHERE sr_returned_date_sk = d_date_sk AND d_year = 2000 GROUP BY sr_customer_sk, sr_store_sk) SELECT c_customer_id FROM customer_total_return ctr1, store, customer WHERE ctr1.ctr_total_return > (SELECT avg(ctr_total_return) * 1.2 FROM customer_total_return ctr2 WHERE ctr1.ctr_store_sk = ctr2.ctr_store_sk) AND s_store_sk = ctr1.ctr_store_sk AND s_state = 'TN' AND ctr1.ctr_customer_sk = c_customer_sk ORDER BY c_customer_id LIMIT 100;"
+  rm -f /tmp/log4j.properties
+}
+
+
+collect_bigdata_omni_shuffle(){
+  spark_path=$1
+  shuffle_jars=$2
+  database=$3
+  shuffle_ock_path=$4
+  # 自定义ock路径
+  cat << EOF > /tmp/ock_spark.conf
+spark.task.cpus 1
+spark.shuffle.compress true
+spark.shuffle.spill.compress true
+spark.rdd.compress true
+spark.executor.extraClassPath     $shuffle_jars
+spark.driver.extraClassPath       $shuffle_jars
+
+spark.driver.extraJavaOptions -Djava.library.path=$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars
+spark.executor.extraJavaOptions -Djava.library.path=$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars
+spark.driver.extraLibraryPath   $shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars:.
+spark.executor.extraLibraryPath $shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/common/ucx/ucx:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/datakit:$shuffle_ock_path/ucache/24.0.0/linux-aarch64/lib/mf:$shuffle_ock_path/jars:.
+
+spark.shuffle.manager              org.apache.spark.shuffle.ock.OCKRemoteShuffleManager
+spark.shuffle.ock.manager true
+spark.shuffle.ock.home $shuffle_ock_path
+spark.shuffle.ock.version 24.0.0
+spark.shuffle.ock.binaryType linux-aarch64
+
+spark.blacklist.enabled true
+spark.files.fetchFailure.unRegisterOutputOnHost true
+spark.shuffle.service.enabled  false
+spark.blacklist.application.fetchFailure.enabled true
+spark.serializer                        org.apache.spark.serializer.KryoSerializer
+EOF
+  timeout 20 $spark_path/bin/spark-sql --deploy-mode client --driver-cores 8 --driver-memory 40G --num-executors 24 --executor-cores 12 --executor-memory 25g --master yarn --conf spark.sql.codegen.wholeStage=false --jars $shuffle_jars --properties-file /tmp/ock_spark.conf --database $database > $log_path/bigdata_omni_shuffle.log 2>&1
+  rm -f /tmp/ock_spark.conf
+}
+
+
+collect_bigdata_components(){
+  spark_path=$1
+  $spark_path/bin/spark-sql --version && echo spark > $log_path/bigdata_components.log
+  hive --version && echo hive >> $log_path/bigdata_components.log
+  hbase version && echo hbase >> $log_path/bigdata_components.log
+}
+
+
+#################HPC特性信息收集##################
+# $1 #用户可执行文件路径
+
+collect_hpc_acceleration_library(){
+    bin_path=$1
+    rm -rf $log_path/hpc_acceleration_library.log
+    touch $log_path/hpc_acceleration_library.log
+    ldd $bin_path > $log_path/hpc_acceleration_library.log  2>&1
+}
+
+# $1 #用户可执行文件路径
+collect_sme_acceleration_library(){
+    bin_path=$1
+    ifsme=`lscpu|grep Flags|grep sme`
+    if [ -n "$ifsme" ]; then
+        bin_path=$1 #用户可执行文件路径
+        rm -rf $log_path/hpc_SME_library.log
+        touch $log_path/hpc_SME_library.log
+        ldd $bin_path | grep SME >> $log_path/hpc_SME_library.log 2>&1
+        objdump -d $bin_path >> $log_path/hpc_SME_library.log 2>&1
+    else
+      echo "架构不支持SME" >> $log_path/hpc_SME_library.log
+    fi
+
+}
+
+collect_sve_source_code(){
+  grep -r arm_sve.h "$1" > $log_path/hpc_sve.log
+}
+
+
+################环境信息收集#######################
+collect_os_msg(){
+    echo  os: $(cat /etc/os-release |grep PRETTY_NAME=|awk -F= '{print $2}') >  $log_path/os_msg.log
+    echo kernel: $(uname -r) >> $log_path/os_msg.log
+    dmidecode -t Processor|grep -m 1 Version: >> $log_path/os_msg.log
+    dmidecode -t system|grep "Product Name" >> $log_path/os_msg.log
+  }
+
+
+main(){
+  select_project=$(acquire_select_project)
+  echo "开始收集BoostKit 特性信息如下：$select_project"
+  mkdir -p $log_path
+  rm -fr $log_path/*
+  echo "日志存放位置： $log_path"
+
+  collect_os_msg
+	for per_project in $select_project
+	do
+	    if [ $per_project = "Arm" ];
+		  then
+		    	kbox_container=$(acquire_value Arm kbox_container)
+	        video_container=$(acquire_value Arm video_container)
+	        instruction_container=$(acquire_value Arm instuction_container)
+	        echo "start collect Arm msg..."
+	        collect_arm_native $kbox_container $video_container $instruction_container
+	        echo "Arm collect msg Done..."
+	    elif [ $per_project = "Virt" ];
+		  then
+			    echo "start collect Virt msg..."
+			    cvm_name=$(acquire_value Virtcca cvm_name)
+          cvm_username=$(acquire_value Virtcca cvm_username)
+          cvm_password=$(acquire_value Virtcca cvm_password)
+          collect_ccos_msg
+          collect_virtcca_msg $cvm_name $cvm_username $cvm_password
+          echo "Virt collect msg Done..."
+		  elif [ $per_project = "Database" ];
+		  then
+		      echo "start collect Database msg..."
+		      use_mysql=$(acquire_value Database use_mysql)
+		      mysql_install_path=$(acquire_value Database mysql_install_path)
+		      mysql_username=$(acquire_value Database mysql_username)
+		      mysql_password=$(acquire_value Database mysql_password)
+		      mysql_port=$(acquire_value Database mysql_port)
+		      database_name=$(acquire_value Database database_name)
+		      nvme_name=$(acquire_value Database nvme_name)
+
+          if [ "$use_mysql" == "1" ]; then
+            collect_database  $mysql_install_path $mysql_username $mysql_password $mysql_port $database_name $nvme_name
+            echo "Database mysql collect msg Done..."
+          else
+            other_db_bin=$(acquire_value Database other_db_bin)
+            greenplum_username=$(acquire_value Database greenplum_username)
+            greenplum_port=$(acquire_value Database greenplum_port)
+            kae_version=$(acquire_value Database kae_version)
+            greenplum_kae_sql=$(acquire_value Database greenplum_kae_sql)
+            collect_database_other_db "$other_db_bin" "$greenplum_username" "$greenplum_password" "$greenplum_port" "$kae_version" "$greenplum_kae_sql"
+            echo "Database other db collect msg Done..."
+          fi
+      elif [ $per_project = "Acclib" ];
+      then
+           echo "start collect acceleration_library msg..."
+           system_lib=$(acquire_value Acclib system_lib)
+           hmpp_lib=$(acquire_value Acclib HMPP_lib)
+           math_lib=$(acquire_value Acclib math_lib)
+           math_jar=$(acquire_value Acclib math_jar)
+           math_java=$(acquire_value Acclib math_java)
+           collect_acceleration_library "$system_lib" "$hmpp_lib" "$math_lib" "$math_jar" "$math_java"
+           echo "acceleration_library collect msg Done..."
+      elif [ $per_project = "Storage" ];
+      then
+          echo "start collect Storage msg..."
+          ec_pool_name=$(acquire_value Storage ec_pool_name)
+          ceph_conf=$(acquire_value Storage ceph_conf)
+          storage_maintain_bin=$(acquire_value Storage storage_maintain_bin)
+          rocksdb_bin=$(acquire_value Storage rocksdb_bin)
+          ucache_bin=$(acquire_value Storage ucache_bin)
+          non_ceph_bin=$(acquire_value Storage non_ceph_bin)
+          non_ceph_pid=$(acquire_value Storage non_ceph_pid)
+          collect_storage_acc "$ec_pool_name" "$ceph_conf" "$storage_maintain_bin" "$rocksdb_bin" "$ucache_bin" "$non_ceph_bin" "$non_ceph_pid"
+          echo "Storage collect msg Done..."
+      elif [ $per_project = "Bigdata" ];
+      then
+          echo "start collect Bigdata msg..."
+          algorithms_path=$(acquire_value Bigdata algorithms_path)
+          algorithms_list=$(acquire_value Bigdata algorithms_name)
+          dataset_list=$(acquire_value Bigdata dataset_list)
+          spark_path=$(acquire_value Bigdata spark_path)
+          database=$(acquire_value Bigdata database)
+          omnioperator_dir=$(acquire_value Bigdata omnioperator_dir)
+          omniadvisor_dir=$(acquire_value Bigdata omniadvisor_dir)
+          mysql_username=$(acquire_value Bigdata mysql_username)
+          mysql_password=$(acquire_value Bigdata mysql_password)
+          mysql_database_name=$(acquire_value Bigdata mysql_database_name)
+          omnimv_dir=$(acquire_value Bigdata omnimv_dir)
+          omnidata_launcher=$(acquire_value Bigdata omnidata_launcher)
+          omnidata_launcher_server=$(acquire_value Bigdata omnidata_launcher_server)
+          omnidata_install_path=$(acquire_value Bigdata omnidata_install_path)
+          push_down_jars=$(acquire_value Bigdata push_down_jars)
+          push_down_conf=$(acquire_value Bigdata push_down_conf)
+          zookeeper_address=$(acquire_value Bigdata zookeeper_address)
+          zookeeper_path=$(acquire_value Bigdata zookeeper_path)
+          shuffle_jars=$(acquire_value Bigdata shuffle_jars)
+          shuffle_ock_path=$(acquire_value Bigdata shuffle_ock_path)
+          collect_bigdata_components $spark_path
+          collect_bigdata_kal "${algorithms_list[@]}" $algorithms_path "${dataset_list[@]}"
+          collect_bigdata_operator $spark_path $database $omnioperator_dir
+          collect_bigdata_hbase
+          collect_bigdata_tune_up $omniadvisor_dir $mysql_username $mysql_password $mysql_database_name
+          collect_bigdata_omnimv "$omnimv_dir"
+          collect_bigdata_omni_push_down "$omnidata_launcher_server" "$omnidata_launcher" "$push_down_jars" "$push_down_conf" "$spark_path" "$database" "$omnidata_install_path" "$zookeeper_address" "$zookeeper_path"
+          collect_bigdata_omni_shuffle "$spark_path" "$shuffle_jars" "$database" "$shuffle_ock_path"
+          echo "Bigdata collect msg Done..."
+      elif [ $per_project = "Virtual" ];
+      then
+        echo "start collect Virtual msg..."
+        collect_virtual_host
+        server_name=$(acquire_value Virtual server_name)
+        network=$(acquire_value Virtual network)
+        flavor=$(acquire_value Virtual flavor)
+        volume=$(acquire_value Virtual volume)
+        availability_zone=$(acquire_value Virtual availability_zone)
+        collect_virtual_dpu $server_name $network $flavor $volume $availability_zone
+        vm_ip=$(acquire_value Virtual vm_ip)
+        vm_user=$(acquire_value Virtual vm_user)
+        vm_password=$(acquire_value Virtual vm_password)
+        vm_ceph_disk_name=$(acquire_value Virtual vm_ceph_disk_name)
+        vm_name=$(acquire_value Virtual vm_name)
+        collect_virtual_ceph "$vm_ip" "$vm_user" "$vm_password" "$vm_ceph_disk_name" "$vm_name"
+        collect_virtual_ovs_xpf
+        echo "Virtual collect msg Done..."
+      elif [ $per_project = "HPC" ];
+      then
+        echo "start collect HPC msg..."
+        acc_lib=$(acquire_value HPC acc_lib)
+        sme=$(acquire_value HPC sme)
+        sve_source_code=$(acquire_value HPC sve_source_code)
+        collect_hpc_acceleration_library $acc_lib
+        collect_sme_acceleration_library $sme
+        collect_sve_source_code $sve_source_code
+        echo "HPC collect msg Done..."
+		fi
+    done
+}
+
+if [ -e $config_file ]; then
+  customer_information=$(acquire_value Global information)
+  check_customer_info $customer_information
+else
+  echo "config.ini not exist"
+  exit 1
+fi
+main
+tar_log_file $customer_information
 
-## 1. **采集工具**
 
-### **1.1采集工具能力说明**
 
 
 
-    用于一键收集鲲鹏使能套件BoostKit 特性使能情况信息，以及系统信息，生成统一压缩包（压缩包包含客户id标识信息以及打包时间信息）。 压缩包用于后续分析出具验收报告
 
-系统信息收集包括：操作系统版本信息、内核版本、鲲鹏服务器的机型
 
-软件信息收集包括：BoostKit 下八个解决方案特性是否生效的关键日志信息。 对于未使能的特性，采集过程中会有报错，是正常现象。
 
-- **注意**：只需修改要采集的特性相关的配置，其余配置保持不变即可
-- **注意**：采集过程中会尝试采集对应解决方案下的所有特性，因此对未使能特性的采集出现报错是正常现象，不影响最终结果
 
 
-### **1.2采集工具配置文件说明**
 
-**文件名称**： config.ini
-
-**位置**: 和采集脚本同级目录
-
-**功能**: 用于控制收集是否采集解决方案特性信息以及 必要用户信息输入
-
-
-
-#### **1.2.1大数据配置文件说明**
-
-
-
-![bigdata](./BoostKit_pic/bigdata.png)
-
-> check=False
-
-check 默认为False, 置为True 则开启大数据相关特性使能信息收集功能
-
- 
-
-> algorithms_path=/home/KAL_TEST_DIR
-
-机器学习和图分析算法加速库安装路径，默认为/home/KAL_TEST_DIR
-
-
-
-> algorithms_name=algorithms_name1  algorithms_name2  algorithms_name3
-
-在$KAL_TEST_DIR/bin/ml/ or $KAL_TEST_DIR/bin/graph/ 目录下有对应 算法名_run.sh 脚本
-
-用户自获取 算法名成填入algorithms_name 对应行，多个算法空格隔开，至少选择四种不同的算法
-
-机器学习和图分析算法加速库的算法名列表，默认为algorithms_name1  algorithms_name2  algorithms_name3
-
-
-
-> dataset_list=dataset1 dataset2 dataset3
-
-机器学习和图分析算法加速库的数据集列表，默认为dataset1 dataset2 dataset3
-
-
-
-> spark_path=/home/
-
-spark的安装路径，默认为/home/
-
-
-
-> database=tpcds_bin_partitioned_orc_1000
-
-所创建对应数据库的名称，根据用户所创建的数据库名称填写，默认为tpcds_bin_partitioned_orc_1000
-
-
-
-> omnioperator_dir=/opt/omni-operator
-
-算子加速的安装路径，默认为/opt/omni-operator
-
-
-
-> omniadvisor_dir=/home
-
-参数调优的安装路径，默认为/home
-
-
-
-> mysql_username=root
-
-可以启动数据库服务的用户名，默认是root用户
-
-
-
-> mysql_password=12345
-
-登录数据库的密码，默认为12345
-
-
-
-> mysql_database_name=xxxxx
-
-所创建对应数据库的名称，根据用户所创建的数据库名称填写
-
-> omnimv_dir=/omnimv
-
-omnimv 目录路径, 用于物化视图特性验证
-
-> omnidata_launcher_server=
-
-launcher 所在服务器的名称 (需可直接ssh无密码访问, 不填则默认在当前服务器上)
-
-> omnidata_launcher=/home/omm/omnidata-install/omnidata/bin/launcher
-
-launcher 二进制路径，用于算子下推特性验证
-
-> omnidata_install_path=/home/omm/omnidata-install
-
-omnidata 安装目录，用于算子下推特性验证
-
-> push_down_jars=/usr/local/spark-plugin-jar/*
-
-算子下推相关jar包路径，用于算子下推特性验证
-
-> push_down_conf=spark.executor.extraClassPath=./*
-
-配置spark参数，用于算子下推特性验证
-
-> zookeeper_address=agent1:2181,agent2:2181,agent3:2181
-
-连接 zookeeper 地址，用于算子下推特性验证
-
-> zookeeper_path=/sdi/status
-
-存放下推资源信息的目录，用于算子下推特性验证
-
-> shuffle_jars=/home/ockadmin/opt/ock/jars/*
-
-shuffle加速相关jar包路径，用于shuffle加速特性验证
-
-> shuffle_ock_path=/home/ockadmin/opt/ock
-
-shuffle加速 ock 安装路径，用于shuffle加速特性验证
-
-#### **1.2.2分布式存储配置文件说明**
-
-![bigdata](./BoostKit_pic/storage.png)
-
-> check=False
-
-check 默认为False, 置为True 则开启分布式存储相关特性使能信息收集功能
-
- 
-
-> ec_pool_name=ec_pool
-
-注：分布式存储加速算法库特性信息收集 需用户自己先创建 ec_pool， **并回填ec_pool_name至配置文件**
-
-创建流程如下：
-
-ceph osd erasure-code-profile set EC-profile k=4 m=2 plugin=ksal
-
-ceph osd pool create ceph_ecpool 32 32 erasure EC-profile
-
-> ceph_conf=/tmp/ceph.conf
-
-ceph 配置文件路径，用于“压缩算法”特性验收
-
-> storage_maintain_bin=/tmp/maintain
-
-用到存储维护工具库特性的二进制路径
-
-> rocksdb_bin=/tmp/rock.bin
-
-用到Rocksdb元数据加速特性的二进制路径
-
-> ucache_bin=/tmp/ucache.bin
-
-用到Ucache智能读缓存特性的二进制路径
-
-> non_ceph_bin=/tmp/non_ceph.bin
-
-非ceph场景下的软件二进制路径，用于“存储加速算法库”特性验收
-
-> non_ceph_pid=38799 
-
-非ceph场景下的软件进程id，用于“存储加速算法库”特性验收
-
- 
-
-#### **1.2.3数据库配置文件说明**
-
-![bigdata](./BoostKit_pic/database.png)
-
-> check=False
-
-check 默认为False, 置为True 则开启数据库相关特性使能信息收集功能
-
-> use_mysql=1
-
-是否 mysql 场景下验收，填1或0
-
-> other_db_bin=/usr/losql/pgsql
-
-非mysql场景下，需填写数据库二进制路径
-
-> mysql_install_path=/usr/local/mysql
-
-数据库安装路径，默认为/usr/local/mysql
-
-> mysql_username=root
-
-可以启动数据库服务的用户名，默认是root用户
-
-> mysql_password=123456
-
-登录数据库的密码，默认为123456
-
-> mysql_port=3306
-
-数据库端口，默认为3306
-
-> nvme_name=nvme0n1
-
-nvme盘名称，用于验收 ”MySQL NVMe SSD原子写“ 特性
-
-> database_name=xxxx
-
-所创建对应数据库的名称，根据用户所创建的数据库名称填写
-
-> greenplum_username=root
-
-greenplum 用户名，用于验收“KAEzip压缩解压缩优化”特性
-
-> greenplum_port=5432
-
-greenplum 端口，用于验收“KAEzip压缩解压缩优化”特性
-
-> kae_version=
-
-kae 版本, 填写1.0或2.0, 用于验收“KAEzip压缩解压缩优化”特性
-
-> greenplum_kae_sql=
-
-greenplum kae sql 语句，用于验收“KAEzip压缩解压缩优化”特性
- 
-
-#### **1.2.4 ARM原生配置文件说明**
-
-![bigdata](./BoostKit_pic/arm_native.png)
-
-> check=False
-
-check 默认为False, 置为True 则开启ARM原生特性使能信息收集功能
-
-> kbox_container=kbox_1
-
-> video_container=android_2
-
-> instuction_container=kbox_3
-
-分别为待采集的kbox、视频流、指令流容器名称。要求3个容器均存在，否则会退出脚本。
-
- 
-
-
-
-#### **1.2.5加速库配置文件说明**
-
-![bigdata](./BoostKit_pic/acc_lib.png)
-
-工具默认支持验收 KAE 特性，配置文件无需修改
-
-> check=False
-
-check 默认为False, 置为True 则开启加速库特性使能信息收集功能
-
-> system_lib=/home/system_bin
-
-引用系统库二进制文件绝对路径
-
-> HMPP_lib=/home/HMPP_bin
-
-引用HMPP库二进制文件绝对路径
-
-> math_lib=/home/math_bin
-
-引用数学库二进制文件绝对路径
-
-> math_jar=/home/math.jar
-
-引用数学库的jar包位置
-
-> math_java=/home/math.class
-
-引用数学库的字节码文件位置
-
-
-#### **1.2.6虚拟化配置文件说明**
-
-![bigdata](./BoostKit_pic/virtual.png)
-
-
-
-注意：
-
-1.OVS流表网卡加速特性需再host测执行，配置文件无需修改
-
-2.虚拟化DPU卸载 特性需要再DPU测执行采集工具， 配置文件无需修改
-
-3.OVS流表归一化 特性验证前需准备环境，让物理机B上的虚拟机持续ping物理机A上的虚拟机，然后在物理机A上运行采集工具
-该特性默认支持验收， 配置文件无需修改
-
-OpenStack 验证需要以下信息
-
-> server_name=vm1
-
-> network=port1_vdpa01
-
-> flavor=4U4G80G
-
-> volume=ceph1_centos2
-
-> availability_zone=nova:dpu01 
-
-> vm_ip=71.14.48.104
-
-虚拟机ip, 用于验收高性能云盘优化特性
-
-> vm_user=root
-
-虚拟机用户名, 用于验收高性能云盘优化特性
-
-> vm_password=Huawei12#$
-
-虚拟机密码, 用于验收高性能云盘优化特性
-
-> vm_ceph_disk_name=vdb
-
-虚拟机使用的高性能云盘名称, 用于验收高性能云盘优化特性
-
-> vm_name=vm1
-
-虚拟机名称, 用于验收高性能云盘优化特性
-
-#### **1.2.7 机密计算配置文件说明**
-
-![bigdata](./BoostKit_pic/virt.png)
-
-> check=False
-
-check 默认为False, 置为True 则开启数据库相关特性使能信息收集功能
-
- 
-
-> cvm_name
-
-机密虚机名称,默认为cvm1
-
-> cvm_username
-
-机密虚机的用户名,默认为root
-
-> cvm_password
-
-机密虚机的用户名密码,默认为huawei
-
- 
-
-#### **1.2.8 HPC配置文件说明**
-
-![bigdata](./BoostKit_pic/hpc.png)
-
-
-
-> check=False
-
-check 默认为False, 置为True 则开启HPC相关特性使能信息收集功能
-
-> acc_lib
-
-引用HPC加速库改造二进制文件绝对路径
-
-> sme
-
-引用HPC SME改造二进制文件绝对路径
-
-> sve_source_code
-
-填写有用到 sve 的源码目录或文件的绝对路径
-
-
-### 1.3 采集工具使用说明
-
-#### 1.3.1 二进制使用
-
-```
-./collect_msg 
-# 同级目录下具有config.ini 配置文件，且已按1.2中对应解决方案完成相关参数配置
-```
-
-#### 1.3.2  shell 脚本使用
-
-```
-bash collect_msg.sh 
-# 同级目录下具有config.ini 配置文件， 且已按1.2中对应解决方案完成相关参数配置
-```
 
-- 
Gitee


From 07fa74dcf1a7493799f941443c4a812c4a002b3b Mon Sep 17 00:00:00 2001
From: ksun <sunkai71@huawei.com>
Date: Fri, 6 Sep 2024 02:58:11 +0000
Subject: [PATCH 4/4] =?UTF-8?q?=E9=87=87=E9=9B=86=E5=B7=A5=E5=85=B7=20?=
 =?UTF-8?q?=E6=96=B0=E5=A2=9E=20config.ini=20=E6=98=93=E7=94=A8=E6=80=A7?=
 =?UTF-8?q?=E8=AF=B4=E6=98=8E?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: ksun <sunkai71@huawei.com>
---
 tools/Boostkit_ISV_Tool.md | 13 ++++++++++---
 1 file changed, 10 insertions(+), 3 deletions(-)

diff --git a/tools/Boostkit_ISV_Tool.md b/tools/Boostkit_ISV_Tool.md
index a1f9677..13a1781 100644
--- a/tools/Boostkit_ISV_Tool.md
+++ b/tools/Boostkit_ISV_Tool.md
@@ -12,6 +12,8 @@
 
 软件信息收集包括：BoostKit 下八个解决方案特性是否生效的关键日志信息。 对于未使能的特性，采集过程中会有报错，是正常现象。
 
+- **注意**：只需修改要采集的特性相关的配置，其余配置保持不变即可
+- **注意**：采集过程中会尝试采集对应解决方案下的所有特性，因此对未使能特性的采集出现报错是正常现象，不影响最终结果
 
 
 ### **1.2采集工具配置文件说明**
@@ -134,6 +136,10 @@ omnidata 安装目录，用于算子下推特性验证
 
 shuffle加速相关jar包路径，用于shuffle加速特性验证
 
+> shuffle_ock_path=/home/ockadmin/opt/ock
+
+shuffle加速 ock 安装路径，用于shuffle加速特性验证
+
 #### **1.2.2分布式存储配置文件说明**
 
 ![bigdata](./BoostKit_pic/storage.png)
@@ -267,15 +273,15 @@ check 默认为False, 置为True 则开启ARM原生特性使能信息收集功
 
 check 默认为False, 置为True 则开启加速库特性使能信息收集功能
 
-> system_lib=/home/system_lib.so
+> system_lib=/home/system_bin
 
 引用系统库二进制文件绝对路径
 
-> HMPP_lib=/home/HMPP_lib.so
+> HMPP_lib=/home/HMPP_bin
 
 引用HMPP库二进制文件绝对路径
 
-> math_lib=/home/math_lib.so 
+> math_lib=/home/math_bin
 
 引用数学库二进制文件绝对路径
 
@@ -397,3 +403,4 @@ check 默认为False, 置为True 则开启HPC相关特性使能信息收集功
 bash collect_msg.sh 
 # 同级目录下具有config.ini 配置文件， 且已按1.2中对应解决方案完成相关参数配置
 ```
+
-- 
Gitee