dbname=$DBNAMEuser=$DBUSRpasswd=$DBPWD#连接数据库db2 connect to $DBNAME user $DBUSR using $DBPWD gt;/dev/nulldb2 set sc
最近由于项目需要,用shell程序批量删除业务表数据,但还需要按业务需求保留业务历史数据,由于项目中用的是db2,db2在删除数据时会产生大量的日志,会把日志文件充满,会报57011错误.通过在网上查找一些资料,最终在不改变原表结构参数的基础上,减少其他们人员的工作量的基础上动态调整参数。
以下为具体操作步骤:
-- db2 delete 大表不写日志操作
1.update command options using c off -- //关闭自动提交
2.alter table MARPT.RPT_DIM_U_ORG_INX_M_CURR_CUS_PRO_TBK activate not logged initially //设置不记日志
3.delete from MARPT.RPT_DIM_U_ORG_INX_M_CURR_CUS_PRO_TBK -- 删除数据
4.commit//手动提交
5.update command options using c on//打开自动提交
相关操作说明;
1.alter table testdeletetab ACTIVATE NOT LOGGED INITIALLY,设置表操作不记日志,这条命令只在一个事务里有效,,遇到commit之后就失效了,这个很需要关注,因为有的时候我们的连接都是设置的自动提交,所以虽然设置了不记日志,但是并没有起到作用。
2.可以通过相关的命令查看当前命令参数
db2 list command options
下边为相应的shell脚本,可以参照一下
. /home/odSUSEr1/.profile
#ODS RUN ALL GDBMA JOBS
#GDBMA
#2011-3-16
#删除表参数
WORK_DATE=$2
TAB_NAME=$1
#
SYSNAME=GDBMA
if [ "$TAB_NAME#" -eq "#" ]
then
echo "the job do not delete the table data!! "
else
MADS_HOME=/home/odsuser1/gdbma/etl
#DS Config
DSConfigFile=$MADS_HOME/dsconfig_gdbma
#MARPT ETL2数据库
#DB
DBNAME=`awk 'FS="=" {if ($0~/^MARPTDBName/) print $2}' $DSConfigFile`
DBUSR=`awk 'FS="=" {if ($0~/^MARPTDBUser/) print $2}' $DSConfigFile`
DBPWD=`awk 'FS="=" {if ($0~/^MARPTDBPassword/) print $2}' $DSConfigFile`
DBSCHEMA=`awk 'FS="=" {if ($0~/^MARPTDBSchema/) print $2}' $DSConfigFile`
DBPWD=`$MADS_HOME/Encrypt/discrypt.sh $DBPWD`
dbname=$DBNAME
user=$DBUSR
passwd=$DBPWD
#连接数据库
db2 connect to $DBNAME user $DBUSR using $DBPWD >/dev/null
db2 set schema=$DBSCHEMA;
ssql="SELECT SCHEDULE,KEEP_DATE,SCH_NAME,TAB_DATE,NO_LOG from "$DBSCHEMA".S_TAB_INFO where tab_name='"$TAB_NAME"' "
SDATA=`db2 -t "$ssql"`
if [ $? -eq 0 ]
then
echo " the job drop data start!"
else
echo "this query false!!!"
fi
echo "$SDATA" | sed -e '4,/^$/!d;/^$/d'|
#循环读取job,然后调度
while read SCHEDULE KEEP_DATE SCH_NAME TAB_DATE NO_LOG
do
echo "$NO_LOG"
if [ "$NO_LOG" = 'Y' ]
then
#参数调整(取消自动提交)
COMMIT_OFF=`db2 -a "update command options using c off"`
#激活不写日志
LOG_OFF=`db2 -a "alter table "$DBSCHEMA"."$TAB_NAME" activate not logged initially"`
# 清数据开始
if [ "$SCHEDULE" = 'M' ]
then
if [ "$KEEP_DATE" = 1 ]
then
delete_table="delete from "$DBSCHEMA"."$TAB_NAME" "
else
v_tx_date=`db2 -x "select DATE(SUBSTR(varchar(date('"$WORK_DATE"')),1,8)||'01') -(int(trim('"$KEEP_DATE"'))-2) MONTHS -1 DAYS from sysibm.sysdummy1 "`
echo "$v_tx_date"
delete_table="delete from "$DBSCHEMA"."$TAB_NAME" where date("$TAB_DATE") = date('"$v_tx_date"')"
fi
fi
if [ "$SCHEDULE" = 'D' ]
then
if [ "$KEEP_DATE" = 1 ]
then
delete_table="delete from "$DBSCHEMA"."$TAB_NAME" "
else
v_tx_date=`db2 -x "select date('"$WORK_DATE"') -(int(trim('"$KEEP_DATE"'))*31) days from sysibm.sysdummy1 "`
delete_table="delete from "$DBSCHEMA"."$TAB_NAME" where date("$TAB_DATE") = date('"$v_tx_date"')"
fi
fi
DELDATA=`db2 -a $delete_table`
echo "$DELDATA" | sed -n -e 's/^.*sqlcode: \([-,0-9][0-9]*\).*/\1/p' | read SQLCODE
if [ $SQLCODE -ge 0 ]
then
echo "the job delete table sucessfull"
else
echo "the job delete table false"
fi
#提交
COMMIT_DATE=`db2 -a "commit"`
#设置自动提交
COMMIT_ON=`db2 -a "update command options using c off"`
else
if [ "$SCHEDULE" = 'M' ]
then
if [ "$KEEP_DATE" = 1 ]
then
delete_table="delete from "$DBSCHEMA"."$TAB_NAME" "
else
v_tx_date=`db2 -x "select ( DATE(SUBSTR(varchar(date('"$WORK_DATE"')),1,8)||'01') -(int(trim('"$KEEP_DATE"'))-2) MONTHS -1 DAYS) from sysibm.sysdummy1"`
delete_table="delete from "$DBSCHEMA"."$TAB_NAME" where date("$TAB_DATE") = date('"$v_tx_date"')"
fi
fi
if [ "$SCHEDULE" = 'D' ]
then
if [ "$KEEP_DATE" = 1 ]
then
delete_table="delete from "$DBSCHEMA"."$TAB_NAME" "
else
v_tx_date=`db2 -x "select date('"$WORK_DATE"') -(int(trim('"$KEEP_DATE"'))*31) days from sysibm.sysdummy1 "`
delete_table="delete from "$DBSCHEMA"."$TAB_NAME" where date("$TAB_DATE") = date('"$v_tx_date"')"
fi
fi
DELDATA=`db2 -a $delete_table`
echo "$DELDATA" | sed -n -e 's/^.*sqlcode: \([-,0-9][0-9]*\).*/\1/p' | read SQLCODE
if [ $SQLCODE -ge 0 ]
then
echo "the job delete table sucessfull"
else
echo "the job delete table false"
fi
fi
done
fi

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.

SQL commands in MySQL can be divided into categories such as DDL, DML, DQL, DCL, etc., and are used to create, modify, delete databases and tables, insert, update, delete data, and perform complex query operations. 1. Basic usage includes CREATETABLE creation table, INSERTINTO insert data, and SELECT query data. 2. Advanced usage involves JOIN for table joins, subqueries and GROUPBY for data aggregation. 3. Common errors such as syntax errors, data type mismatch and permission problems can be debugged through syntax checking, data type conversion and permission management. 4. Performance optimization suggestions include using indexes, avoiding full table scanning, optimizing JOIN operations and using transactions to ensure data consistency.

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MySQL's position in databases and programming is very important. It is an open source relational database management system that is widely used in various application scenarios. 1) MySQL provides efficient data storage, organization and retrieval functions, supporting Web, mobile and enterprise-level systems. 2) It uses a client-server architecture, supports multiple storage engines and index optimization. 3) Basic usages include creating tables and inserting data, and advanced usages involve multi-table JOINs and complex queries. 4) Frequently asked questions such as SQL syntax errors and performance issues can be debugged through the EXPLAIN command and slow query log. 5) Performance optimization methods include rational use of indexes, optimized query and use of caches. Best practices include using transactions and PreparedStatemen

MySQL is suitable for small and large enterprises. 1) Small businesses can use MySQL for basic data management, such as storing customer information. 2) Large enterprises can use MySQL to process massive data and complex business logic to optimize query performance and transaction processing.

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