SQL优化选对执行计划,查询速度提升1000倍 | OceanBase 应用实践

作者:爱可生数据库高级工程师任仲禹,擅长故障分析和性能优化。

本文通过一个案例,分享使用OceanBase时,SQL走错执行计划,而导致慢SQL的排查方法论。

案例背景

在使用OceanBase 3.2.3 版本的过程中,项目组反映某个 SELECT 语句在指定时间内的查询响应速度异常缓慢,其耗时远超正常情况的1000倍以上。具体细节如下:

  • 慢 SELECT

    SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '1900-01-01' AND ACCTG_DT <= '2025-03-31' ;

  • 关键表结构、记录数信息如下

    -- 脱敏处理
    show create table renzy\G
    *************************** 1. row ***************************
    Table: renzy
    Create Table: CREATE TABLE renzy (
    ID char(18) COLLATE utf8mb4_bin NOT NULL COMMENT ,
    ...
    ACCT_NO char(40) COLLATE utf8mb4_bin NOT NULL COMMENT ,
    ...
    ACCTG_DT date DEFAULT NULL COMMENT ,
    ...
    PRIMARY KEY (ID),
    ...
    KEY renzy_I2 (ACCT_NO) BLOCK_SIZE 16384 LOCAL,
    ...
    KEY renzy_I5 (ACCTG_DT, ENQ_INST_CD, BLON_INST_CD, EMRG_STPY_SRC_CD) BLOCK_SIZE 16384 LOCAL,
    ...
    ) DEFAULT CHARSET = utf8mb4;
    1 row in set (0.01 sec)

    MySQL > SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882');
    +---------+
    | TOT_CNT |
    +---------+
    | 1 |
    +---------+
    1 row in set (0.02 sec)

    MySQL > SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE ACCTG_DT >= '1900-01-01' AND ACCTG_DT <= '2025-03-31';
    +----------+
    | TOT_CNT |
    +----------+
    | 25432155 |
    +----------+
    1 row in set (12.42 sec)

    MySQL > SELECT COUNT(*) AS TOT_CNT FROM renzy;
    +----------+
    | TOT_CNT |
    +----------+
    | 25435024 |
    +----------+
    1 row in set (10.65 sec)

排查过程

正常执行不慢

MySQL > select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '1900-01-01' AND ACCTG_DT <= '2025-03-31') as orginal limit 2000; select last_trace_id();
+---------+
| TOT_CNT |
+---------+
|       1 |
+---------+
1 row in set (0.02 sec)

以下是执行计划,从中可见,索引I2是最高效的选择,它在进行等值匹配时仅需要执行一次回表操作。

*************************** 1. row ***************************
Query Plan: ========================================================
|ID|OPERATOR        |NAME               |EST. ROWS|COST|
--------------------------------------------------------
|0 |LIMIT           |                   |1        |92  |
|1 | SCALAR GROUP BY|                   |1        |92  |
|2 |  TABLE SCAN    |renzy(renzy_I2)|1        |92  |
========================================================
...
Outline Data:
-------------------------------------
  /*+
      BEGIN_OUTLINE_DATA
      INDEX(@"SEL$2" "gabsdb.renzy"@"SEL$2" "renzy_I2")
      END_OUTLINE_DATA
  */
...
renzy:table_rows:25419080, physical_range_rows:1, logical_range_rows:1, index_back_rows:1, output_rows:0, est_method:local_storage, optimization_method=cost_based, avaiable_index_name[renzy_I2,renzy_I5], pruned_index_name[renzy_I1,renzy_I3,renzy_I4,renzy_I6], unstable_index_name[renzy], estimation info[table_id:1105009185965290, (table_type:1, version:0-1699898410195654-1699898410195654, logical_rc:1, physical_rc:1), (table_type:7, version:1699898401860480-1699898401860480-1699898433101378, logical_rc:0, physical_rc:0), (table_type:7, version:1699898433101378-1699904137032515-1699905915658079, logical_rc:0, physical_rc:0), (table_type:5, version:1699898433101378-1699904137032515-1699905915658079, logical_rc:0, physical_rc:0), (table_type:0, version:1699905915658079-1699905915658079-9223372036854775807, logical_rc:0, physical_rc:0)]
...

通过 OCP 的 SQL 诊断获取慢 SQL 的 plan_id,检查慢 SQL 实际命中的 plan。

MySQL [oceanbase]> select * from gv$plan_cache_plan_stat where plan_id=7288229 \G                                                                         
*************************** 1. row ***************************
...
              plan_id: 7288229
...
            statement: select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = ?) AND LAWENF_NTIST_TP_CD NOT LIKE ? AND LAWENF_NTIST_TP_CD NOT LIKE ? AND EMRG_STPY_SRC_CD != ? AND ACCTG_DT >= ? AND ACCTG_DT <= ?) as orginal limit 2000
            query_sql: select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '' AND ACCTG_DT <= '') as orginal limit 2000
       special_params: 2000
          param_infos: {1,0,0,-1,22},{1,0,0,-1,22},{1,0,0,-1,22},{1,0,0,-1,22},{1,0,0,-1,22},{1,0,0,-1,22},{1,0,0,-1,22},{1,0,0,-1,22},{1,0,0,-1,22},{1,0,0,-1,22},{1,0,0,-1,17},{1,0,0,-1,17}
             sys_vars: 45,45,12582912,2,4,1,0,0,32,3,1,0,1,1,0,10485760,1,1,0,1,BINARY,BINARY,AL32UTF8,AL16UTF16,BYTE,FALSE,1,100,64,200,0,13,NULL,1,1,1,1
            plan_hash: 10428103352368081688
      first_load_time: 2023-11-14 10:14:11.578250
       schema_version: 1699927892190832
       merged_version: 287
     last_active_time: 2023-11-14 11:04:58.127020
         avg_exe_usec: 35858760
     slowest_exe_time: 2023-11-14 11:04:58.127020
     slowest_exe_usec: 171575101
           slow_count: 2
            hit_count: 7
            plan_size: 81984
           executions: 8
           disk_reads: 1136285
        direct_writes: 0
          buffer_gets: 18067948
application_wait_time: 0
concurrency_wait_time: 0
    user_io_wait_time: 0
       rows_processed: 8
         elapsed_time: 286870087
             cpu_time: 229807460
         large_querys: 2
 delayed_large_querys: 1
    delayed_px_querys: 0
      outline_version: 0
           outline_id: -1
         outline_data: /*+ BEGIN_OUTLINE_DATA INDEX(@"SEL$2" "gabsdb.renzy"@"SEL$2" "renzy_I5") END_OUTLINE_DATA*/
....
1 row in set (0.09 sec)

MySQL [oceanbase]> select * from oceanbase.gv$plan_cache_plan_explain where tenant_id=1005 and port=2882 and plan_id=7288229 and ip='12.240.26.70'\G
....
PLAN_LINE_ID: 2
    OPERATOR:   PHY_TABLE_SCAN
        NAME: renzy(renzy_I5)
        ROWS: 0
        COST: 91
    PROPERTY: table_rows:25419080, physical_range_rows:1, logical_range_rows:1, index_back_rows:0, output_rows:0, est_method:local_storage, avaiable_index_name[renzy_I2,renzy_I5]
...

上述结果的关键信息如下

1.query_sql :为该plan第一次执行时的SQL语句。

2.first_load_time :缓存该plan并hit的时间。

3.slowest_exe_usec :该计划的最慢耗时。

4.outline_id : 是否命中了绑定的outline,-1即未命中。

5.statement :参数化后的SQL语句。

6.name : 该plan走的索引。

分析下第一次的SQL为啥要走 I5 索引

通过下面执行计划和执行耗时可知,第一次执行的语句因为字段 ACCTG_DT 检索不到数据,所以走 I5 效率最高。

MySQL > explain extended select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '' AND ACCTG_DT <= '') as orginal limit 2000\G
*************************** 1. row ***************************
Query Plan: ========================================================
|ID|OPERATOR        |NAME               |EST. ROWS|COST|
--------------------------------------------------------
|0 |LIMIT           |                   |1        |92  |
|1 | SCALAR GROUP BY|                   |1        |92  |
|2 |  TABLE SCAN    |renzy(renzy_I5)|0        |92  |
========================================================
Outline Data:
-------------------------------------
  /*+
      BEGIN_OUTLINE_DATA
      INDEX(@"SEL$2" "gabsdb.renzy"@"SEL$2" "renzy_I5")
      END_OUTLINE_DATA
  */
renzy:table_rows:25419080, physical_range_rows:1, logical_range_rows:1, index_back_rows:0, output_rows:0, est_method:local_storage, optimization_method=cost_based, avaiable_index_name[renzy_I2,renzy_I5], pruned_index_name[renzy_I1,renzy_I3,renzy_I4,renzy_I6], unstable_index_name[renzy]

MySQL > select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '' AND ACCTG_DT <= '') as orginal limit 2000;
+---------+
| TOT_CNT |
+---------+
|       0 |
+---------+
1 row in set, 2 warnings (0.02 sec)

分析下后续SQL为何不淘汰该plan

我们知道,SQL查询并不需要每次生成查询计划,因为这样涉及到硬解析等耗费性能的操作,所以默认每次会先查询 Plan Cache (硬解析操作包含词法/语法/语义解析,优化器统计信息查询等步骤,参考下图)。

本案例中,后续的SQL命中该 Plan 就可以理解,因为要走 I5 索引,range太大基本为全索引扫描,所以耗时太慢。,

ACCTG_DT >= '1900-01-01' AND ACCTG_DT <= '2025-03-31'

什么时候淘汰这个计划呢?

// 关键代码段如下(410bp1社区版,这里的逻辑和323bp8企业版类似,企业版代码不便贴出)
if (sample_count < SLOW_QUERY_SAMPLE_SIZE) {
        // do nothing when query execution samples are not enough
      } else {
        if (stat_.cpu_time_ <= SLOW_QUERY_TIME_FOR_PLAN_EXPIRE * stat_.execute_times_) {
        // do nothing for fast query
        } else if (is_plan_unstable(sample_count, sample_exec_row_count, sample_exec_usec)) {
          set_is_expired(true);
        }
        ATOMIC_STORE(&(stat_.sample_times_), 0);
      }
    }

bool ObPhysicalPlan::is_plan_unstable(const int64_t sample_count,
                                      const int64_t sample_exec_row_count,
                                      const int64_t sample_exec_usec)
{
  bool bret = false;
  if (sample_exec_usec <= SLOW_QUERY_TIME_FOR_PLAN_EXPIRE * sample_count) {
    // sample query is fast query in the average
  } else if (OB_PHY_PLAN_LOCAL == plan_type_) {
    int64_t first_query_range_rows = ATOMIC_LOAD(&stat_.first_exec_row_count_);
    if (sample_exec_row_count <= SLOW_QUERY_ROW_COUNT_THRESOLD * sample_count) {
      // the sample query does not accesses too many rows in the average
    } else if (sample_exec_row_count / sample_count > first_query_range_rows * 10) {
      // the average sample query range row count increases great
      bret = true;
      LOG_INFO("local query plan is expired due to unstable performance",
               K(bret), K(stat_.execute_times_),
               K(first_query_range_rows), K(sample_exec_row_count), K(sample_count));
    }
  } else if ( OB_PHY_PLAN_DISTRIBUTED == plan_type_) {
    int64_t first_exec_usec = ATOMIC_LOAD(&stat_.first_exec_usec_);
    if (sample_exec_usec / sample_count > first_exec_usec * 2) {
      // the average sample query execute time increases great
      bret = true;
      LOG_INFO("distribute query plan is expired due to unstable performance",
               K(bret), K(stat_.execute_times_), K(first_exec_usec),
               K(sample_exec_usec), K(sample_count));
    }
  } else {
    // do nothing
  }
  return bret;
}

这里淘汰一个 Plan 需要满足的条件有2个:

  • sample_count < SLOW_QUERY_SAMPLE_SIZE)
  • sample_exec_row_count / sample_count > first_query_range_rows * 10

这里的 SLOW_QUERY_SAMPLE_SIZE 是常量,OB410的定义是 20;sample_count(采样次数)实质为Plan的SQL执行次数。

static const int64_t SLOW_QUERY_SAMPLE_SIZE = 20; // smaller than ObPlanStat::MAX_SCAN_STAT_SIZE

结合上下文代码来看,意思是满足如下情况就会淘汰Plan:

  • 命中该Plan的SQL执行大于等于20次。
  • (执行的SQL扫描总行数 / 执行次数) 大于 (第一次SQL执行扫描的行数 * 10)

复现以验证

1.清空 plan cache,执行业务第一次生成 Plan 的 SQL。

MySQL > alter system flush plan cache;
Query OK, 0 rows affected (0.13 sec)

MySQL > select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '' AND ACCTG_DT <= '') as orginal limit 2000;
+---------+
| TOT_CNT |
+---------+
|       0 |
+---------+
1 row in set, 2 warnings (0.02 sec)

2.执行业务 SQL,复现慢的情况。

MySQL > select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '1900-01-01' AND ACCTG_DT <= '2025-03-31') as orginal limit 2000;
+---------+
| TOT_CNT |
+---------+
|       1 |
+---------+
1 row in set (2 min 51.61 sec)

MySQL > select last_trace_id();
+-----------------------------------+
| last_trace_id()                   |
+-----------------------------------+
| YB420CF01A46-0006009AD91C51ED-0-0 |
+-----------------------------------+
1 row in set (0.04 sec)

MySQL > select * from oceanbase.gv$sql_audit where trace_id='YB420CF01A46-0006009AD91C51ED-0-0'\G                                                                                                         ...
               TRACE_ID: YB420CF01A46-0006009AD91C51ED-0-0
...
                 SQL_ID: 2B53F4C1C330C2C089C7518CD71D667A
              QUERY_SQL: select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '1900-01-01' AND ACCTG_DT <= '2025-03-31') as orginal limit 2000
...
           ELAPSED_TIME: 171575101
...
           EXECUTE_TIME: 171574843
...
MEMSTORE_READ_ROW_COUNT: 25416176
 SSSTORE_READ_ROW_COUNT: 50832349
...

这里通过 sql_audit 可以观测到重要的信息:

  • ELAPSED_TIME : 执行耗时。

  • MEMSTORE_READ_ROW_COUNT / SSSTORE_READ_ROW_COUNT : 这条SQL扫描的行数。

    MySQL [oceanbase]> select * from gv$plan_cache_plan_stat where plan_id=7289113 \G
    *************************** 1. row ***************************
    ...
    sql_id: 2B53F4C1C330C2C089C7518CD71D667A
    ...
    statement: select * from (SELECT COUNT() AS TOT_CNT FROM renzy WHERE (ACCT_NO = ?) AND LAWENF_NTIST_TP_CD NOT LIKE ? AND LAWENF_NTIST_TP_CD NOT LIKE ? AND EMRG_STPY_SRC_CD != ? AND ACCTG_DT >= ? AND ACCTG_DT <= ?) as orginal limit 2000
    query_sql: select * from (SELECT COUNT(
    ) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '' AND ACCTG_DT <= '') as orginal limit 2000
    ...
    outline_id: -1
    outline_data: /+ BEGIN_OUTLINE_DATA INDEX(@"SEL$2" "gabsdb.renzy"@"SEL$2" "renzy_I5") END_OUTLINE_DATA/
    ...

通过 plan_cache_plan_stat 可看到这条SQL命中了第一次SQL执行时生成的 Plan(不符合预期)。

3.继续通过脚本执行多次。

#!/bin/bash
for i in `seq 1 30`
do
echo ">>> do  $i"
mysql -h12.240.68.36 -P3306 -uroot@tgabsua2g00#obcdcbsuat01 -pOceanBase_123# -Dgabsdb -A -c -NBe "select now();select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '1900-01-01' AND ACCTG_DT <= '2025-03-31') as orginal limit 2000; select last_trace_id();select now();"
done

# ./1.sh
...
>>> do  17       # 耗时 2分钟27s 命中
2023-11-14 16:05:36
1
YB420CF01A46-0006009B016C66EE-0-0
2023-11-14 16:08:03
>>> do  18       # 耗时 2min12s  命中
2023-11-14 16:08:03
1
YB420CF01A46-0006009AFF8FF46D-0-0
2023-11-14 16:10:15
>>> do  19       # 耗时 2min36s  命中
2023-11-14 16:10:15
1
YB420CF01A46-0006009B012FF1D0-0-0
2023-11-14 16:12:51
>>> do  20        # 耗时 1s内     未命中,恢复正常
2023-11-14 16:12:51
1
YB420CF01A46-0006009AFEBDA7C6-0-0
2023-11-14 16:12:51
>>> do  21
2023-11-14 16:12:51
1
YB420CF01A46-0006009B016F1561-0-0
2023-11-14 16:12:52
...

可以观察到,命中该 Plan 的SQL 执行次数大于 20 次(含手工执行)后,该"不符合预期的" Plan 被淘汰。

  1. 再次执行的SQL的 sql_audit 和 plan_cache_plan_stat,可看到重新生成了 Plan。

    MySQL > select * from oceanbase.gv$sql_audit where trace_id='YB420CF01A46-0006009AFEBDA7C6-0-0'\G
    SQL_ID: 2B53F4C1C330C2C089C7518CD71D667A
    QUERY_SQL: select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '1900-01-01' AND ACCTG_DT <= '2025-03-31') as orginal limit 2000
    ...
    ELAPSED_TIME: 207
    PLAN_ID: 7334178
    ...
    MEMSTORE_READ_ROW_COUNT: 1
    SSSTORE_READ_ROW_COUNT: 2

    MySQL [oceanbase]> select * from gv$plan_cache_plan_stat where plan_id=7334178 \G
    *************************** 1. row ***************************
    ...
    plan_id: 7334178
    sql_id: 2B53F4C1C330C2C089C7518CD71D667A
    ...
    statement: select * from (SELECT COUNT() AS TOT_CNT FROM renzy WHERE (ACCT_NO = ?) AND LAWENF_NTIST_TP_CD NOT LIKE ? AND LAWENF_NTIST_TP_CD NOT LIKE ? AND EMRG_STPY_SRC_CD != ? AND ACCTG_DT >= ? AND ACCTG_DT <= ?) as orginal limit 2000
    query_sql: select * from (SELECT COUNT(
    ) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '1900-01-01' AND ACCTG_DT <= '2025-03-31') as orginal limit 2000
    ...
    first_load_time: 2023-11-14 16:12:51.547434
    ...
    slowest_exe_time: 2023-11-14 16:12:51.547618
    slowest_exe_usec: 4139
    ...
    elapsed_time: 8279
    ...
    outline_id: -1
    outline_data: /+ BEGIN_OUTLINE_DATA INDEX(@"SEL$2" "gabsdb.renzy"@"SEL$2" "renzy_I2") END_OUTLINE_DATA/
    ...

5.obs日志关键信息

#grep YB420CF01A46-0006009B012FF1D0-0-0 observer.log.20231114161*|less
observer.log.20231114161017:[2023-11-14 16:10:15.813150] INFO  [SQL] ob_sql.cpp:1769 [86881][0][YB420CF01A46-0006009B012FF1D0-0-0] [lt=17] [dc=0] It is a large query, need delay, do not need disconnect(avg_process_time=123860984, exec_cnt=20, large_query_threshold=5000000, plan->get_plan_id()=7328133, ret=-4023)
observer.log.20231114161017:[2023-11-14 16:10:15.813208] TRACE [TRACE]obmp_base.cpp:156 [86881][0][YB420CF01A46-0006009B012FF1D0-0-0] [lt=18] [dc=0] [packet retry query](TRACE=begin_ts=1699949415813080 2023-11-14 08:10:15.813080|[start_sql] u=0 addr:{ip:"12.241.29.28", port:16606}|[process_begin] u=0 addr:{ip:"12.241.29.28", port:16606}, in_queue_time:13, receive_ts:1699949415813066, enqueue_ts:1699949415813067, trace_id:YB420CF01A46-0006009B012FF1D0-0-0|[session] u=3 sid:3221784053, tenant_id:1005|[parse_begin] u=10 stmt:"select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '1900-01-01' AND ACCTG_DT <= '2025-03-31') as orginal limit 2000", stmt_len:287|[process_end] u=85 run_ts:1699949415813082|total_timeu=98)
observer.log.20231114161302:[2023-11-14 16:12:51.412696] INFO  [SQL.ENG] ob_physical_plan.cpp:736 [86881][0][YB420CF01A46-0006009B012FF1D0-0-0] [lt=15] [dc=0] local query plan is expired due to unstable performance(bret=true, stat_.execute_times_=21, first_query_range_rows=0, sample_exec_row_count=1525906500, sample_count=20)
observer.log.20231114161302:[2023-11-14 16:12:51.412725] WARN  [SHARE.SCHEMA] revert (ob_schema_mgr_cache.cpp:131) [86881][0][YB420CF01A46-0006009B012FF1D0-0-0] [lt=11] [dc=0] long time to hold one guard(schema_mgr=0x7ee87934c610, tenant_id=1, version=1697523399752200, cur_timestamp=1699949571412714, ref_timestamp=1699949415812628, lbt()="0xf51231f 0x6158f04 0x4f5992c 0x50c61cc 0x4ed2f6f 0x4ecf518 0x4ecc8ef 0x4ecaa6e 0xb8c71f1 0x4ec9c90 0xb8c4d31 0x4ec58f6 0xb8c52a7 0xf3f17f3 0xf3f164f 0xf6901df")
observer.log.20231114161302:[2023-11-14 16:12:51.412738] WARN  [SHARE.SCHEMA] revert (ob_schema_mgr_cache.cpp:131) [86881][0][YB420CF01A46-0006009B012FF1D0-0-0] [lt=8] [dc=0] long time to hold one guard(schema_mgr=0x7edddba39170, tenant_id=1005, version=1699931135472584, cur_timestamp=1699949571412734, ref_timestamp=1699949415812628, lbt()="0xf51231f 0x6158f04 0x4f5992c 0x50c61cc 0x4ed2f6f 0x4ecf518 0x4ecc8ef 0x4ecaa6e 0xb8c71f1 0x4ec9c90 0xb8c4d31 0x4ec58f6 0xb8c52a7 0xf3f17f3 0xf3f164f 0xf6901df")
observer.log.20231114161302:[2023-11-14 16:12:51.412798] TRACE [TRACE]obmp_base.cpp:147 [86881][0][YB420CF01A46-0006009B012FF1D0-0-0] [lt=5] [dc=0] [slow query](TRACE=begin_ts=1699949415813229 2023-11-14 08:10:15.813229|[start_sql] u=0 addr:{ip:"12.241.29.28", port:16606}|[process_begin] u=0 addr:{ip:"12.241.29.28", port:16606}, in_queue_time:162, receive_ts:1699949415813066, enqueue_ts:1699949415813225, trace_id:YB420CF01A46-0006009B012FF1D0-0-0|[session] u=2 sid:3221784053, tenant_id:1005|[parse_begin] u=6 stmt:"select * from (SELECT COUNT(*) AS TOT_CNT FROM renzy WHERE (ACCT_NO = '6222620117273900882') AND LAWENF_NTIST_TP_CD NOT LIKE '12%' AND LAWENF_NTIST_TP_CD NOT LIKE '05%' AND EMRG_STPY_SRC_CD != 'JZ05' AND ACCTG_DT >= '1900-01-01' AND ACCTG_DT <= '2025-03-31') as orginal limit 2000", stmt_len:287|[exec_begin] u=29 arg1:false, end_trans_cb:false, plan_id:7328133|[do_open_plan_begin] u=8 |[sql_start_stmt_begin] u=1 |[sql_start_participant_begin] u=5 |[storage_table_scan_begin] u=56 |[storage_table_scan_end] u=116 |[get_row] u=155437570 |[result_set_close] u=161554 |[close_plan_begin] u=0 |[revert_scan_iter] u=96 |[end_participant_begin] u=3 |[start_end_stmt] u=1 |[affected_rows] u=0 affected_rows:-1|[store_found_rows] u=1 found_rows:0, return_rows:1|[auto_end_plan_begin] u=0 |[process_end] u=86 run_ts:1699949415813230|total_timeu=155599534)

第21次执行的SQL的关键日志信息:

[2023-11-14 16:12:51.412696] INFO  [SQL.ENG] ob_physical_plan.cpp:736 [86881][0][YB420CF01A46-0006009B012FF1D0-0-0] [lt=15] [dc=0] local query plan is expired due to unstable performance(bret=true, stat_.execute_times_=21, first_query_range_rows=0, sample_exec_row_count=1525906500, sample_count=20)

由该日志,关键信息如下:

  1. sample_exec_row_count=1525906500

  2. sample_count=20

  3. first_query_range_rows=0

结合代码可知该结果满足 Plan 淘汰条件,从而 plan expire。

sample_exec_row_count / sample_count > first_query_range_rows * 10

1525906500 / 20  > 0 * 10  
// 这里 1525906500 的结果,不难得知,是单次SQL扫描行数 * 20. 
// 即(25416176 + 50832349) * 20 = 1524970500 约等于 1525906500 
 MEMSTORE_READ_ROW_COUNT: 25416176
 SSSTORE_READ_ROW_COUNT: 50832349

结论

1.本例主要是想分享SQL走错 Plan 而SQL慢的排查方法论,问题原因还是比较简单,重点是和大家分享处理OB遇到类似问题的思路等。

2.本例问题在当前OB 323版本中没有好的优化方式,给到的建议是:

  • 如果 I5 索引业务上未使用场景,则删除。
  • 绑定 outline,使该SQL走 I2 索引。

3.分享下OB中 Plan Cache 清理策略:

  • 手工清理

    -- 租户内执⾏,清除当前租户中所有 Plan Cache。⽣产慎⽤。
    ALTER SYSTEM FLUSH PLAN CACHE;
    -- sys租户下执⾏,不同粒度。
    ALTER SYSTEM FLUSH PLAN CACHE TENANT = 'T_MySQL';
    ALTER SYSTEM FLUSH PLAN CACHE sql_id='B601070DFC14CB85FDA3766A69A9E1B3'
    databases='myob1' tenant='tenant1' GLOBAL;

  • 自动清理 ob_plan_cache_percentage 参数控制 Plan Cache占用租户内存的百分比。 本例中提到

  1. sample_count < SLOW_QUERY_SAMPLE_SIZE) :命中该Plan的SQL执行大于等于20次。

2.sample_exec_row_count / sample_count > first_query_range_rows * 10 :(执行的SQL扫描总行数 / 执行次数) 大于 (第一次SQL执行扫描的行数 * 10)

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