避免表扫描,而在查询中使用索引

时间:2019-05-28 19:31:57

标签: mysql indexing vitess

我正在设计一个新的数据库,并且注意到我的查询没有按预期扩展。当我的汇总涉及数百条记录时,我发现响应时间显着增加。我想知道我的查询是否存在严重缺陷,或者我只是没有使用正确的索引。

我对查询做了很多调整,但是还没有想出一种消除全表扫描而使用索引的方法。当我在查询中使用类似于EXPLAIN的工具时,会看到以下内容:

  • 全表扫描通常效率低下,请避免使用它们。
  • 您的查询使用MySQL的“文件排序”操作。这往往会降低查询速度。
  • 您的查询使用MySQL的临时表。这可能需要额外的I / O,并会减慢查询速度。

表格:

CREATE TABLE `indexTable` (
  `id` int(10) unsigned NOT NULL,
  `userId` int(10) unsigned NOT NULL,
  `col1` varbinary(320) NOT NULL,
  `col2` tinyint(3) unsigned NOT NULL,
  `col3` tinyint(3) unsigned NOT NULL,
  `createdAt` bigint(20) unsigned NOT NULL,
  `updatedAt` bigint(20) unsigned NOT NULL,
  `metadata` json NOT NULL,
  PRIMARY KEY (`id`,`userId`,`col1`,`col2`,`col3`),
  KEY `createdAt` (`createdAt`),
  KEY `id_userId_col1_col2_createdAt` (`id`,`userId`,`col1`,`col2`,`createdAt`),
  KEY `col1_col2_createdAt` (`col1`,`col2`,`createdAt`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8

查询:

SELECT t1.id, t1.userId, t1.col1, t1.col2, t1.col3, t1.metadata
FROM indexTable as t1
INNER JOIN(
    SELECT col1, col2, MAX(createdAt) AS maxCreatedAt
    FROM indexTable
    WHERE id = ? AND userId = ?
    GROUP BY col1, col2
    ORDER BY maxCreatedAt
    LIMIT 10 OFFSET 0) AS sub
ON t1.col1 = sub.col1
AND t1.col2 = sub.col2
AND t1.createdAt = sub.maxCreatedAt
WHERE t1.id = ? AND t1.userId = ?
ORDER BY t1.createdAt;

PK:id, userId, col1, col2, col3 索引:createdAt

说明:

{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "34.50"
    },
    "ordering_operation": {
      "using_temporary_table": true,
      "using_filesort": true,
      "cost_info": {
        "sort_cost": "10.00"
      },
      "nested_loop": [
        {
          "table": {
            "table_name": "sub",
            "access_type": "ALL",
            "rows_examined_per_scan": 10,
            "rows_produced_per_join": 10,
            "filtered": "100.00",
            "cost_info": {
              "read_cost": "10.50",
              "eval_cost": "2.00",
              "prefix_cost": "12.50",
              "data_read_per_join": "3K"
            },
            "used_columns": [
              "col1",
              "col2",
              "maxCreatedAt"
            ],
            "attached_condition": "(`sub`.`maxCreatedAt` is not null)",
            "materialized_from_subquery": {
              "using_temporary_table": true,
              "dependent": false,
              "cacheable": true,
              "query_block": {
                "select_id": 2,
                "cost_info": {
                  "query_cost": "10.27"
                },
                "ordering_operation": {
                  "using_filesort": true,
                  "grouping_operation": {
                    "using_temporary_table": true,
                    "using_filesort": false,
                    "table": {
                      "table_name": "indexTable",
                      "access_type": "ref",
                      "possible_keys": [
                        "PRIMARY",
                        "createdAt",
                        "id_userId_col1_col2_createdAt",
                        "col1_col2_createdAt"
                      ],
                      "key": "PRIMARY",
                      "used_key_parts": [
                        "id",
                        "userId"
                      ],
                      "key_length": "8",
                      "ref": [
                        "const",
                        "const"
                      ],
                      "rows_examined_per_scan": 46,
                      "rows_produced_per_join": 46,
                      "filtered": "100.00",
                      "cost_info": {
                        "read_cost": "1.07",
                        "eval_cost": "9.20",
                        "prefix_cost": "10.27",
                        "data_read_per_join": "16K"
                      },
                      "used_columns": [
                        "id",
                        "userId",
                        "createdAt",
                        "col1",
                        "col2",
                        "col3"
                      ],
                      "attached_condition": "((`MyDB`.`indexTable`.`id` <=> 53) and (`MyDB`.`indexTable`.`userId` <=> 549814))"
                    }
                  }
                }
              }
            }
          }
        },
        {
          "table": {
            "table_name": "t1",
            "access_type": "ref",
            "possible_keys": [
              "PRIMARY",
              "createdAt",
              "id_userId_col1_col2_createdAt",
              "col1_col2_createdAt"
            ],
            "key": "id_userId_col1_col2_createdAt",
            "used_key_parts": [
              "id",
              "userId",
              "col1",
              "col2",
              "createdAt"
            ],
            "key_length": "339",
            "ref": [
              "const",
              "const",
              "sub.col1",
              "sub.col2",
              "sub.maxCreatedAt"
            ],
            "rows_examined_per_scan": 1,
            "rows_produced_per_join": 10,
            "filtered": "100.00",
            "cost_info": {
              "read_cost": "10.00",
              "eval_cost": "2.00",
              "prefix_cost": "24.50",
              "data_read_per_join": "3K"
            },
            "used_columns": [
              "id",
              "userId",
              "createdAt",
              "updatedAt",
              "col1",
              "col2",
              "col3",
              "metadata",
            ]
          }
        }
      ]
    }
  }
}

此查询查找col1col2分组中的最新记录,按createdAt排序,并将条目限制为10。

2 个答案:

答案 0 :(得分:0)

“派生”表(子查询)需要此复合索引:

INDEX(id, userid,  -- in either order
      col1, col2,  -- in this order
      createdAt)   -- to make it "covering"

使用该索引,可能可能不会进行全表扫描。但是,它涉及一个文件排序。这是因为ORDER BYGROUP BY不同,它是一个聚合。

t1的需求

INDEX(col1, col2,  -- in either order
      createdAt)

sub,maxCreatedAt-错字?

ORDER BY t1.createdAt-另一个必要文件排序。

不要提防文件排序。尤其是当只有10行时(如第二种情况)。

没有看到SHOW CREATE TABLE,我不能说“文件排序”和“临时表”是否完全接触了磁盘,还是在RAM中完成了。

FORCE INDEX几乎总是一个坏主意-即使对今天有帮助,但明天可能会受到伤害。

如果需要查看过多的表,优化器将故意(正确地)使用表扫描-比在索引和数据之间跳动要快。

答案 1 :(得分:0)

我能够通过更新查询以在id中包含userIdGROUP BY来解决此问题。然后,我能够加入另外两列,并且由于某种原因使MySQL使用了正确的索引。