或一些应用的俄罗斯方块学。
一切新事物都被遗忘了。
题词。
制定问题
需要定期从 AWS 云端下载当前的 PostgreSQL 日志文件到本地 Linux 主机。 不是实时的,但是,我们应该说,稍有延迟。
日志文件更新下载周期为 5 分钟。
AWS 中的日志文件每小时轮换一次。
使用的工具
为了将日志文件上传到主机,使用了一个调用 AWS API 的 bash 脚本“
选项:
- --db-instance-identifier:AWS中的实例名称;
- --log-file-name:当前生成的日志文件名
- --max-item:命令输出中返回的项目总数。下载文件的块大小。
- --starting-token:起始令牌token
是的,而且很简单 - 在工作时间内进行培训和多样化的有趣任务。
我假设问题已经通过常规解决了。 但是快速 Google 并没有提出解决方案,也没有特别希望进行更深入的搜索。 无论如何,这是一个很好的锻炼。
任务正式化
最终的日志文件是一组可变长度的行。 从图形上看,日志文件可以这样表示:
它是否已经让你想起了什么? “俄罗斯方块”是怎么回事? 这就是什么。
如果我们以图形方式表示加载下一个文件时出现的可能选项(为简单起见,在这种情况下,让行具有相同的长度),我们得到 标准俄罗斯方块数字:
1) 该文件是完整下载的并且是最终的。 块大小大于最终文件大小:
2) 该文件有一个延续。 块大小小于最终文件大小:
3) 该文件是前一个文件的延续,并且有一个延续。 块大小小于最终文件其余部分的大小:
4) 该文件是前一个文件的延续,是最终文件。 块大小大于最终文件其余部分的大小:
任务是组装一个矩形或在新的水平上玩俄罗斯方块。
解决问题过程中出现的问题
1) 粘上一串 2 部分
一般来说,没有特别的问题。 初始编程课程中的标准任务。
最佳份量
但这有点有趣。
不幸的是,无法在起始块标签之后使用偏移量:
如您所知,选项 --starting-token 用于指定从哪里开始分页。 此选项采用字符串值,这意味着如果您尝试在 Next Token 字符串前面添加偏移值,则该选项将不会被视为偏移量。
因此,您必须分块阅读。
如果你阅读大部分,那么阅读的数量将是最少的,但数量将是最大的。
如果分小段阅读,则相反,阅读次数最多,但阅读量最少。
因此,为了减少流量和解决方案的整体美观,我不得不想出某种解决方案,不幸的是,它看起来有点像拐杖。
为了说明,让我们考虑在两个大大简化的版本中下载日志文件的过程。 两种情况下的读数数量取决于份量。
1) 小份装载:
2) 大份装载:
和往常一样,最优解在中间.
部分尺寸极小,但在阅读过程中,可以增加尺寸以减少阅读次数。
需要注意的是 read part的最佳大小选择问题尚未完全解决,需要更深入的研究和分析。 也许晚一点。
实施的一般描述
使用过的服务表
CREATE TABLE endpoint
(
id SERIAL ,
host text
);
TABLE database
(
id SERIAL ,
…
last_aws_log_time text ,
last_aws_nexttoken text ,
aws_max_item_size integer
);
last_aws_log_time — временная метка последнего загруженного лог-файла в формате YYYY-MM-DD-HH24.
last_aws_nexttoken — текстовая метка последней загруженной порции.
aws_max_item_size- эмпирическим путем, подобранный начальный размер порции.
脚本全文
下载aws_piece.sh
#!/bin/bash
#########################################################
# download_aws_piece.sh
# downloan piece of log from AWS
# version HABR
let min_item_size=1024
let max_item_size=1048576
let growth_factor=3
let growth_counter=1
let growth_counter_max=3
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh:''STARTED'
AWS_LOG_TIME=$1
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh:AWS_LOG_TIME='$AWS_LOG_TIME
database_id=$2
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh:database_id='$database_id
RESULT_FILE=$3
endpoint=`psql -h MONITOR_ENDPOINT.rds.amazonaws.com -U USER -d MONITOR_DATABASE_DATABASE -A -t -c "select e.host from endpoint e join database d on e.id = d.endpoint_id where d.id = $database_id "`
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh:endpoint='$endpoint
db_instance=`echo $endpoint | awk -F"." '{print toupper($1)}'`
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh:db_instance='$db_instance
LOG_FILE=$RESULT_FILE'.tmp_log'
TMP_FILE=$LOG_FILE'.tmp'
TMP_MIDDLE=$LOG_FILE'.tmp_mid'
TMP_MIDDLE2=$LOG_FILE'.tmp_mid2'
current_aws_log_time=`psql -h MONITOR_ENDPOINT.rds.amazonaws.com -U USER -d MONITOR_DATABASE -A -t -c "select last_aws_log_time from database where id = $database_id "`
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh:current_aws_log_time='$current_aws_log_time
if [[ $current_aws_log_time != $AWS_LOG_TIME ]];
then
is_new_log='1'
if ! psql -h MONITOR_ENDPOINT.rds.amazonaws.com -U USER -d MONITOR_DATABASE -v ON_ERROR_STOP=1 -A -t -q -c "update database set last_aws_log_time = '$AWS_LOG_TIME' where id = $database_id "
then
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: FATAL_ERROR - update database set last_aws_log_time .'
exit 1
fi
else
is_new_log='0'
fi
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh:is_new_log='$is_new_log
let last_aws_max_item_size=`psql -h MONITOR_ENDPOINT.rds.amazonaws.com -U USER -d MONITOR_DATABASE -A -t -c "select aws_max_item_size from database where id = $database_id "`
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: last_aws_max_item_size='$last_aws_max_item_size
let count=1
if [[ $is_new_log == '1' ]];
then
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: START DOWNLOADING OF NEW AWS LOG'
if ! aws rds download-db-log-file-portion
--max-items $last_aws_max_item_size
--region REGION
--db-instance-identifier $db_instance
--log-file-name error/postgresql.log.$AWS_LOG_TIME > $LOG_FILE
then
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: FATAL_ERROR - Could not get log from AWS .'
exit 2
fi
else
next_token=`psql -h MONITOR_ENDPOINT.rds.amazonaws.com -U USER -d MONITOR_DATABASE -v ON_ERROR_STOP=1 -A -t -c "select last_aws_nexttoken from database where id = $database_id "`
if [[ $next_token == '' ]];
then
next_token='0'
fi
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: CONTINUE DOWNLOADING OF AWS LOG'
if ! aws rds download-db-log-file-portion
--max-items $last_aws_max_item_size
--starting-token $next_token
--region REGION
--db-instance-identifier $db_instance
--log-file-name error/postgresql.log.$AWS_LOG_TIME > $LOG_FILE
then
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: FATAL_ERROR - Could not get log from AWS .'
exit 3
fi
line_count=`cat $LOG_FILE | wc -l`
let lines=$line_count-1
tail -$lines $LOG_FILE > $TMP_MIDDLE
mv -f $TMP_MIDDLE $LOG_FILE
fi
next_token_str=`cat $LOG_FILE | grep NEXTTOKEN`
next_token=`echo $next_token_str | awk -F" " '{ print $2}' `
grep -v NEXTTOKEN $LOG_FILE > $TMP_FILE
if [[ $next_token == '' ]];
then
cp $TMP_FILE $RESULT_FILE
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: NEXTTOKEN NOT FOUND - FINISH '
rm $LOG_FILE
rm $TMP_FILE
rm $TMP_MIDDLE
rm $TMP_MIDDLE2
exit 0
else
psql -h MONITOR_ENDPOINT.rds.amazonaws.com -U USER -d MONITOR_DATABASE -v ON_ERROR_STOP=1 -A -t -q -c "update database set last_aws_nexttoken = '$next_token' where id = $database_id "
fi
first_str=`tail -1 $TMP_FILE`
line_count=`cat $TMP_FILE | wc -l`
let lines=$line_count-1
head -$lines $TMP_FILE > $RESULT_FILE
###############################################
# MAIN CIRCLE
let count=2
while [[ $next_token != '' ]];
do
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: count='$count
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: START DOWNLOADING OF AWS LOG'
if ! aws rds download-db-log-file-portion
--max-items $last_aws_max_item_size
--starting-token $next_token
--region REGION
--db-instance-identifier $db_instance
--log-file-name error/postgresql.log.$AWS_LOG_TIME > $LOG_FILE
then
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: FATAL_ERROR - Could not get log from AWS .'
exit 4
fi
next_token_str=`cat $LOG_FILE | grep NEXTTOKEN`
next_token=`echo $next_token_str | awk -F" " '{ print $2}' `
TMP_FILE=$LOG_FILE'.tmp'
grep -v NEXTTOKEN $LOG_FILE > $TMP_FILE
last_str=`head -1 $TMP_FILE`
if [[ $next_token == '' ]];
then
concat_str=$first_str$last_str
echo $concat_str >> $RESULT_FILE
line_count=`cat $TMP_FILE | wc -l`
let lines=$line_count-1
tail -$lines $TMP_FILE >> $RESULT_FILE
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: NEXTTOKEN NOT FOUND - FINISH '
rm $LOG_FILE
rm $TMP_FILE
rm $TMP_MIDDLE
rm $TMP_MIDDLE2
exit 0
fi
if [[ $next_token != '' ]];
then
let growth_counter=$growth_counter+1
if [[ $growth_counter -gt $growth_counter_max ]];
then
let last_aws_max_item_size=$last_aws_max_item_size*$growth_factor
let growth_counter=1
fi
if [[ $last_aws_max_item_size -gt $max_item_size ]];
then
let last_aws_max_item_size=$max_item_size
fi
psql -h MONITOR_ENDPOINT.rds.amazonaws.com -U USER -d MONITOR_DATABASE -A -t -q -c "update database set last_aws_nexttoken = '$next_token' where id = $database_id "
concat_str=$first_str$last_str
echo $concat_str >> $RESULT_FILE
line_count=`cat $TMP_FILE | wc -l`
let lines=$line_count-1
#############################
#Get middle of file
head -$lines $TMP_FILE > $TMP_MIDDLE
line_count=`cat $TMP_MIDDLE | wc -l`
let lines=$line_count-1
tail -$lines $TMP_MIDDLE > $TMP_MIDDLE2
cat $TMP_MIDDLE2 >> $RESULT_FILE
first_str=`tail -1 $TMP_FILE`
fi
let count=$count+1
done
#
#################################################################
exit 0
带有一些解释的脚本片段:
脚本输入参数:
- YYYY-MM-DD-HH24 格式的日志文件名的时间戳:AWS_LOG_TIME=$1
- 数据库 ID:database_id=$2
- 收集的日志文件名:RESULT_FILE=$3
获取上次上传日志文件的时间戳:
current_aws_log_time=`psql -h MONITOR_ENDPOINT.rds.amazonaws.com -U USER -d MONITOR_DATABASE -A -t -c "select last_aws_log_time from database where id = $database_id "`
如果最后加载的日志文件的时间戳与输入参数不匹配,则加载一个新的日志文件:
if [[ $current_aws_log_time != $AWS_LOG_TIME ]];
then
is_new_log='1'
if ! psql -h ENDPOINT.rds.amazonaws.com -U USER -d MONITOR_DATABASE -v ON_ERROR_STOP=1 -A -t -c "update database set last_aws_log_time = '$AWS_LOG_TIME' where id = $database_id "
then
echo '***download_aws_piece.sh -FATAL_ERROR - update database set last_aws_log_time .'
exit 1
fi
else
is_new_log='0'
fi
我们从加载的文件中获取 nexttoken 标签的值:
next_token_str=`cat $LOG_FILE | grep NEXTTOKEN`
next_token=`echo $next_token_str | awk -F" " '{ print $2}' `
下载结束的标志是nexttoken为空值。
在一个循环中,我们计算文件的各个部分,沿途连接行并增加该部分的大小:
主循环
# MAIN CIRCLE
let count=2
while [[ $next_token != '' ]];
do
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: count='$count
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: START DOWNLOADING OF AWS LOG'
if ! aws rds download-db-log-file-portion
--max-items $last_aws_max_item_size
--starting-token $next_token
--region REGION
--db-instance-identifier $db_instance
--log-file-name error/postgresql.log.$AWS_LOG_TIME > $LOG_FILE
then
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: FATAL_ERROR - Could not get log from AWS .'
exit 4
fi
next_token_str=`cat $LOG_FILE | grep NEXTTOKEN`
next_token=`echo $next_token_str | awk -F" " '{ print $2}' `
TMP_FILE=$LOG_FILE'.tmp'
grep -v NEXTTOKEN $LOG_FILE > $TMP_FILE
last_str=`head -1 $TMP_FILE`
if [[ $next_token == '' ]];
then
concat_str=$first_str$last_str
echo $concat_str >> $RESULT_FILE
line_count=`cat $TMP_FILE | wc -l`
let lines=$line_count-1
tail -$lines $TMP_FILE >> $RESULT_FILE
echo $(date +%Y%m%d%H%M)': download_aws_piece.sh: NEXTTOKEN NOT FOUND - FINISH '
rm $LOG_FILE
rm $TMP_FILE
rm $TMP_MIDDLE
rm $TMP_MIDDLE2
exit 0
fi
if [[ $next_token != '' ]];
then
let growth_counter=$growth_counter+1
if [[ $growth_counter -gt $growth_counter_max ]];
then
let last_aws_max_item_size=$last_aws_max_item_size*$growth_factor
let growth_counter=1
fi
if [[ $last_aws_max_item_size -gt $max_item_size ]];
then
let last_aws_max_item_size=$max_item_size
fi
psql -h MONITOR_ENDPOINT.rds.amazonaws.com -U USER -d MONITOR_DATABASE -A -t -q -c "update database set last_aws_nexttoken = '$next_token' where id = $database_id "
concat_str=$first_str$last_str
echo $concat_str >> $RESULT_FILE
line_count=`cat $TMP_FILE | wc -l`
let lines=$line_count-1
#############################
#Get middle of file
head -$lines $TMP_FILE > $TMP_MIDDLE
line_count=`cat $TMP_MIDDLE | wc -l`
let lines=$line_count-1
tail -$lines $TMP_MIDDLE > $TMP_MIDDLE2
cat $TMP_MIDDLE2 >> $RESULT_FILE
first_str=`tail -1 $TMP_FILE`
fi
let count=$count+1
done
接下来是什么?
这样,第一个中间任务——“从云端下载日志文件”就解决了。 下载的日志怎么办?
首先,您需要解析日志文件并从中提取实际请求。
任务不是很困难。 最简单的 bash 脚本就可以了。
上传日志查询.sh
#!/bin/bash
#########################################################
# upload_log_query.sh
# Upload table table from dowloaded aws file
# version HABR
###########################################################
echo 'TIMESTAMP:'$(date +%c)' Upload log_query table '
source_file=$1
echo 'source_file='$source_file
database_id=$2
echo 'database_id='$database_id
beginer=' '
first_line='1'
let "line_count=0"
sql_line=' '
sql_flag=' '
space=' '
cat $source_file | while read line
do
line="$space$line"
if [[ $first_line == "1" ]]; then
beginer=`echo $line | awk -F" " '{ print $1}' `
first_line='0'
fi
current_beginer=`echo $line | awk -F" " '{ print $1}' `
if [[ $current_beginer == $beginer ]]; then
if [[ $sql_flag == '1' ]]; then
sql_flag='0'
log_date=`echo $sql_line | awk -F" " '{ print $1}' `
log_time=`echo $sql_line | awk -F" " '{ print $2}' `
duration=`echo $sql_line | awk -F" " '{ print $5}' `
#replace ' to ''
sql_modline=`echo "$sql_line" | sed 's/'''/''''''/g'`
sql_line=' '
################
#PROCESSING OF THE SQL-SELECT IS HERE
if ! psql -h ENDPOINT.rds.amazonaws.com -U USER -d DATABASE -v ON_ERROR_STOP=1 -A -t -c "select log_query('$ip_port',$database_id , '$log_date' , '$log_time' , '$duration' , '$sql_modline' )"
then
echo 'FATAL_ERROR - log_query '
exit 1
fi
################
fi #if [[ $sql_flag == '1' ]]; then
let "line_count=line_count+1"
check=`echo $line | awk -F" " '{ print $8}' `
check_sql=${check^^}
#echo 'check_sql='$check_sql
if [[ $check_sql == 'SELECT' ]]; then
sql_flag='1'
sql_line="$sql_line$line"
ip_port=`echo $sql_line | awk -F":" '{ print $4}' `
fi
else
if [[ $sql_flag == '1' ]]; then
sql_line="$sql_line$line"
fi
fi #if [[ $current_beginer == $beginer ]]; then
done
现在您可以使用从日志文件中提取的查询。
并且有几种有用的可能性。
解析后的查询必须存储在某个地方。 为此,使用服务表。 日志查询
CREATE TABLE log_query
(
id SERIAL ,
queryid bigint ,
query_md5hash text not null ,
database_id integer not null ,
timepoint timestamp without time zone not null,
duration double precision not null ,
query text not null ,
explained_plan text[],
plan_md5hash text ,
explained_plan_wo_costs text[],
plan_hash_value text ,
baseline_id integer ,
ip text ,
port text
);
ALTER TABLE log_query ADD PRIMARY KEY (id);
ALTER TABLE log_query ADD CONSTRAINT queryid_timepoint_unique_key UNIQUE (queryid, timepoint );
ALTER TABLE log_query ADD CONSTRAINT query_md5hash_timepoint_unique_key UNIQUE (query_md5hash, timepoint );
CREATE INDEX log_query_timepoint_idx ON log_query (timepoint);
CREATE INDEX log_query_queryid_idx ON log_query (queryid);
ALTER TABLE log_query ADD CONSTRAINT database_id_fk FOREIGN KEY (database_id) REFERENCES database (id) ON DELETE CASCADE ;
解析后的请求在 plpgsql 职能 ”日志查询“。
日志查询.sql
--log_query.sql
--verison HABR
CREATE OR REPLACE FUNCTION log_query( ip_port text ,log_database_id integer , log_date text , log_time text , duration text , sql_line text ) RETURNS boolean AS $$
DECLARE
result boolean ;
log_timepoint timestamp without time zone ;
log_duration double precision ;
pos integer ;
log_query text ;
activity_string text ;
log_md5hash text ;
log_explain_plan text[] ;
log_planhash text ;
log_plan_wo_costs text[] ;
database_rec record ;
pg_stat_query text ;
test_log_query text ;
log_query_rec record;
found_flag boolean;
pg_stat_history_rec record ;
port_start integer ;
port_end integer ;
client_ip text ;
client_port text ;
log_queryid bigint ;
log_query_text text ;
pg_stat_query_text text ;
BEGIN
result = TRUE ;
RAISE NOTICE '***log_query';
port_start = position('(' in ip_port);
port_end = position(')' in ip_port);
client_ip = substring( ip_port from 1 for port_start-1 );
client_port = substring( ip_port from port_start+1 for port_end-port_start-1 );
SELECT e.host , d.name , d.owner_pwd
INTO database_rec
FROM database d JOIN endpoint e ON e.id = d.endpoint_id
WHERE d.id = log_database_id ;
log_timepoint = to_timestamp(log_date||' '||log_time,'YYYY-MM-DD HH24-MI-SS');
log_duration = duration:: double precision;
pos = position ('SELECT' in UPPER(sql_line) );
log_query = substring( sql_line from pos for LENGTH(sql_line));
log_query = regexp_replace(log_query,' +',' ','g');
log_query = regexp_replace(log_query,';+','','g');
log_query = trim(trailing ' ' from log_query);
log_md5hash = md5( log_query::text );
--Explain execution plan--
EXECUTE 'SELECT dblink_connect(''LINK1'',''host='||database_rec.host||' dbname='||database_rec.name||' user=DATABASE password='||database_rec.owner_pwd||' '')';
log_explain_plan = ARRAY ( SELECT * FROM dblink('LINK1', 'EXPLAIN '||log_query ) AS t (plan text) );
log_plan_wo_costs = ARRAY ( SELECT * FROM dblink('LINK1', 'EXPLAIN ( COSTS FALSE ) '||log_query ) AS t (plan text) );
PERFORM dblink_disconnect('LINK1');
--------------------------
BEGIN
INSERT INTO log_query
(
query_md5hash ,
database_id ,
timepoint ,
duration ,
query ,
explained_plan ,
plan_md5hash ,
explained_plan_wo_costs ,
plan_hash_value ,
ip ,
port
)
VALUES
(
log_md5hash ,
log_database_id ,
log_timepoint ,
log_duration ,
log_query ,
log_explain_plan ,
md5(log_explain_plan::text) ,
log_plan_wo_costs ,
md5(log_plan_wo_costs::text),
client_ip ,
client_port
);
activity_string = 'New query has logged '||
' database_id = '|| log_database_id ||
' query_md5hash='||log_md5hash||
' , timepoint = '||to_char(log_timepoint,'YYYYMMDD HH24:MI:SS');
RAISE NOTICE '%',activity_string;
PERFORM pg_log( log_database_id , 'log_query' , activity_string);
EXCEPTION
WHEN unique_violation THEN
RAISE NOTICE '*** unique_violation *** query already has logged';
END;
SELECT queryid
INTO log_queryid
FROM log_query
WHERE query_md5hash = log_md5hash AND
timepoint = log_timepoint;
IF log_queryid IS NOT NULL
THEN
RAISE NOTICE 'log_query with query_md5hash = % and timepoint = % has already has a QUERYID = %',log_md5hash,log_timepoint , log_queryid ;
RETURN result;
END IF;
------------------------------------------------
RAISE NOTICE 'Update queryid';
SELECT *
INTO log_query_rec
FROM log_query
WHERE query_md5hash = log_md5hash AND timepoint = log_timepoint ;
log_query_rec.query=regexp_replace(log_query_rec.query,';+','','g');
FOR pg_stat_history_rec IN
SELECT
queryid ,
query
FROM
pg_stat_db_queries
WHERE
database_id = log_database_id AND
queryid is not null
LOOP
pg_stat_query = pg_stat_history_rec.query ;
pg_stat_query=regexp_replace(pg_stat_query,'n+',' ','g');
pg_stat_query=regexp_replace(pg_stat_query,'t+',' ','g');
pg_stat_query=regexp_replace(pg_stat_query,' +',' ','g');
pg_stat_query=regexp_replace(pg_stat_query,'$.','%','g');
log_query_text = trim(trailing ' ' from log_query_rec.query);
pg_stat_query_text = pg_stat_query;
--SELECT log_query_rec.query like pg_stat_query INTO found_flag ;
IF (log_query_text LIKE pg_stat_query_text) THEN
found_flag = TRUE ;
ELSE
found_flag = FALSE ;
END IF;
IF found_flag THEN
UPDATE log_query SET queryid = pg_stat_history_rec.queryid WHERE query_md5hash = log_md5hash AND timepoint = log_timepoint ;
activity_string = ' updated queryid = '||pg_stat_history_rec.queryid||
' for log_query with id = '||log_query_rec.id
;
RAISE NOTICE '%',activity_string;
EXIT ;
END IF ;
END LOOP ;
RETURN result ;
END
$$ LANGUAGE plpgsql;
处理时,使用服务表 pg_stat_db_queries一个包含表中当前查询的快照的 pg_stat_历史记录 (此处描述了表格用法 -
TABLE pg_stat_db_queries
(
database_id integer,
queryid bigint ,
query text ,
max_time double precision
);
TABLE pg_stat_history
(
…
database_id integer ,
…
queryid bigint ,
…
max_time double precision ,
…
);
该函数允许您实现许多有用的功能来处理来自日志文件的请求。 即:
机会 #1 - 查询执行历史
对于启动性能事件非常有用。 首先,了解一下历史——经济放缓是从什么时候开始的?
然后,根据经典,寻找外因。 可能只是数据库负载急剧增加,与具体请求无关。
向 log_query 表添加新条目
port_start = position('(' in ip_port);
port_end = position(')' in ip_port);
client_ip = substring( ip_port from 1 for port_start-1 );
client_port = substring( ip_port from port_start+1 for port_end-port_start-1 );
SELECT e.host , d.name , d.owner_pwd
INTO database_rec
FROM database d JOIN endpoint e ON e.id = d.endpoint_id
WHERE d.id = log_database_id ;
log_timepoint = to_timestamp(log_date||' '||log_time,'YYYY-MM-DD HH24-MI-SS');
log_duration = to_number(duration,'99999999999999999999D9999999999');
pos = position ('SELECT' in UPPER(sql_line) );
log_query = substring( sql_line from pos for LENGTH(sql_line));
log_query = regexp_replace(log_query,' +',' ','g');
log_query = regexp_replace(log_query,';+','','g');
log_query = trim(trailing ' ' from log_query);
RAISE NOTICE 'log_query=%',log_query ;
log_md5hash = md5( log_query::text );
--Explain execution plan--
EXECUTE 'SELECT dblink_connect(''LINK1'',''host='||database_rec.host||' dbname='||database_rec.name||' user=DATABASE password='||database_rec.owner_pwd||' '')';
log_explain_plan = ARRAY ( SELECT * FROM dblink('LINK1', 'EXPLAIN '||log_query ) AS t (plan text) );
log_plan_wo_costs = ARRAY ( SELECT * FROM dblink('LINK1', 'EXPLAIN ( COSTS FALSE ) '||log_query ) AS t (plan text) );
PERFORM dblink_disconnect('LINK1');
--------------------------
BEGIN
INSERT INTO log_query
(
query_md5hash ,
database_id ,
timepoint ,
duration ,
query ,
explained_plan ,
plan_md5hash ,
explained_plan_wo_costs ,
plan_hash_value ,
ip ,
port
)
VALUES
(
log_md5hash ,
log_database_id ,
log_timepoint ,
log_duration ,
log_query ,
log_explain_plan ,
md5(log_explain_plan::text) ,
log_plan_wo_costs ,
md5(log_plan_wo_costs::text),
client_ip ,
client_port
);
功能 #2 - 保存查询执行计划
此时可能会出现反对-澄清-评论:“但是已经有自动解释”。 是的,是的,但是如果执行计划存储在同一个日志文件中并且为了将其保存以供进一步分析,您必须解析日志文件,这有什么意义呢?
但是,我需要:
第一:将执行计划存放在监控数据库的service表中;
其次:能够相互比较执行计划,以便立即看到查询执行计划已更改。
具有特定执行参数的请求可用。 使用 EXPLAIN 获取和存储其执行计划是一项基本任务。
而且,使用EXPLAIN(COSTS FALSE)表达式,可以得到计划的框架,将用于获取计划的哈希值,有助于后续分析执行计划的变化历史。
获取执行计划模板
--Explain execution plan--
EXECUTE 'SELECT dblink_connect(''LINK1'',''host='||database_rec.host||' dbname='||database_rec.name||' user=DATABASE password='||database_rec.owner_pwd||' '')';
log_explain_plan = ARRAY ( SELECT * FROM dblink('LINK1', 'EXPLAIN '||log_query ) AS t (plan text) );
log_plan_wo_costs = ARRAY ( SELECT * FROM dblink('LINK1', 'EXPLAIN ( COSTS FALSE ) '||log_query ) AS t (plan text) );
PERFORM dblink_disconnect('LINK1');
机会 #3 - 使用查询日志进行监控
由于性能指标不是针对请求文本配置的,而是针对其 ID 配置的,因此您需要将日志文件中的请求与配置了性能指标的请求相关联。
好吧,至少为了有一个性能事件发生的确切时间。
这样,当一个请求ID发生性能事件时,就会有一个特定请求的引用,有特定的参数值,以及请求的准确执行时间和时长。 仅使用视图获取给定信息 pg_stat_语句 - 这是被禁止的。
找到查询的queryid并更新log_query表中的条目
SELECT *
INTO log_query_rec
FROM log_query
WHERE query_md5hash = log_md5hash AND timepoint = log_timepoint ;
log_query_rec.query=regexp_replace(log_query_rec.query,';+','','g');
FOR pg_stat_history_rec IN
SELECT
queryid ,
query
FROM
pg_stat_db_queries
WHERE
database_id = log_database_id AND
queryid is not null
LOOP
pg_stat_query = pg_stat_history_rec.query ;
pg_stat_query=regexp_replace(pg_stat_query,'n+',' ','g');
pg_stat_query=regexp_replace(pg_stat_query,'t+',' ','g');
pg_stat_query=regexp_replace(pg_stat_query,' +',' ','g');
pg_stat_query=regexp_replace(pg_stat_query,'$.','%','g');
log_query_text = trim(trailing ' ' from log_query_rec.query);
pg_stat_query_text = pg_stat_query;
--SELECT log_query_rec.query like pg_stat_query INTO found_flag ;
IF (log_query_text LIKE pg_stat_query_text) THEN
found_flag = TRUE ;
ELSE
found_flag = FALSE ;
END IF;
IF found_flag THEN
UPDATE log_query SET queryid = pg_stat_history_rec.queryid WHERE query_md5hash = log_md5hash AND timepoint = log_timepoint ;
activity_string = ' updated queryid = '||pg_stat_history_rec.queryid||
' for log_query with id = '||log_query_rec.id
;
RAISE NOTICE '%',activity_string;
EXIT ;
END IF ;
END LOOP ;
后记
因此,所描述的方法已在
虽然,当然,在我个人看来,仍然有必要研究用于选择和更改下载部分大小的算法。 一般情况下这个问题还没有解决。 这可能会很有趣。
但那是一个完全不同的故事......
来源: habr.com