CREATE TABLE t0 (
i1 INTEGER
);
INSERT INTO t0 VALUE (0),(1),(2),(3),(4),(5),(6),(7),(8),(9);
CREATE TABLE t1 (
pk INTEGER PRIMARY KEY,
i1 INTEGER NOT NULL,
c1 CHAR(250),
c2 CHAR(250),
c3 CHAR(250),
c4 CHAR(250),
INDEX i1_key (i1)
) ENGINE=XENGINE;
INSERT INTO t1
SELECT a0.i1 + 10 * a1.i1, a0.i1, 'abc', 'def', 'ghi', 'jkl'
FROM t0 AS a0, t0 AS a1;
ANALYZE TABLE t1;
Table	Op	Msg_type	Msg_text
test.t1	analyze	status	OK
EXPLAIN FORMAT=JSON SELECT * FROM t1;
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "13.75"
    },
    "table": {
      "table_name": "t1",
      "access_type": "ALL",
      "rows_examined_per_scan": 100,
      "rows_produced_per_join": 100,
      "filtered": "100.00",
      "cost_info": {
        "read_cost": "3.75",
        "eval_cost": "10.00",
        "prefix_cost": "13.75",
        "data_read_per_join": "392K"
      },
      "used_columns": [
        "pk",
        "i1",
        "c1",
        "c2",
        "c3",
        "c4"
      ]
    }
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1`
#
# Test that updating the cost constants does not influence on an
# existing connection
#
UPDATE mysql.server_cost
SET cost_value=0.4
WHERE cost_name="row_evaluate_cost";
FLUSH OPTIMIZER_COSTS;
#
# The cost estimates should not have changed
#
EXPLAIN FORMAT=JSON SELECT * FROM t1;
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "13.75"
    },
    "table": {
      "table_name": "t1",
      "access_type": "ALL",
      "rows_examined_per_scan": 100,
      "rows_produced_per_join": 100,
      "filtered": "100.00",
      "cost_info": {
        "read_cost": "3.75",
        "eval_cost": "10.00",
        "prefix_cost": "13.75",
        "data_read_per_join": "392K"
      },
      "used_columns": [
        "pk",
        "i1",
        "c1",
        "c2",
        "c3",
        "c4"
      ]
    }
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1`
UPDATE mysql.server_cost
SET cost_value=DEFAULT;
#
# Test effect of changing the row_evalute_cost
#
UPDATE mysql.server_cost
SET cost_value=0.2
WHERE cost_name="row_evaluate_cost";
FLUSH OPTIMIZER_COSTS;
#
# Verify that the cost estimate for evalution cost has doubled
#
EXPLAIN FORMAT=JSON SELECT * FROM t1;
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "23.75"
    },
    "table": {
      "table_name": "t1",
      "access_type": "ALL",
      "rows_examined_per_scan": 100,
      "rows_produced_per_join": 100,
      "filtered": "100.00",
      "cost_info": {
        "read_cost": "3.75",
        "eval_cost": "20.00",
        "prefix_cost": "23.75",
        "data_read_per_join": "392K"
      },
      "used_columns": [
        "pk",
        "i1",
        "c1",
        "c2",
        "c3",
        "c4"
      ]
    }
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1`
UPDATE mysql.server_cost
SET cost_value=DEFAULT;
#
# Test effect of changing key_compare_cost
#
# Use a query that will use loose index scan since loose index scan
# is comparing keys in order to determine group boundaries.
# Result from running query with default cost constants:
#
EXPLAIN FORMAT=JSON SELECT DISTINCT(i1) FROM t1;
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "13.00"
    },
    "duplicates_removal": {
      "using_filesort": false,
      "table": {
        "table_name": "t1",
        "access_type": "range",
        "possible_keys": [
          "i1_key"
        ],
        "key": "i1_key",
        "used_key_parts": [
          "i1"
        ],
        "key_length": "4",
        "rows_examined_per_scan": 51,
        "rows_produced_per_join": 51,
        "filtered": "100.00",
        "using_index_for_group_by": true,
        "cost_info": {
          "read_cost": "7.90",
          "eval_cost": "5.10",
          "prefix_cost": "13.00",
          "data_read_per_join": "200K"
        },
        "used_columns": [
          "pk",
          "i1"
        ]
      }
    }
  }
}
Warnings:
Note	1003	/* select#1 */ select distinct `test`.`t1`.`i1` AS `i1` from `test`.`t1`
UPDATE mysql.server_cost
SET cost_value=0.1
WHERE cost_name="key_compare_cost";
FLUSH OPTIMIZER_COSTS;
#
# Verify that the cost estimate for read cost is increased
#
EXPLAIN FORMAT=JSON SELECT DISTINCT(i1) FROM t1;
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "13.75"
    },
    "duplicates_removal": {
      "using_filesort": false,
      "table": {
        "table_name": "t1",
        "access_type": "index",
        "possible_keys": [
          "i1_key"
        ],
        "key": "i1_key",
        "used_key_parts": [
          "i1"
        ],
        "key_length": "4",
        "rows_examined_per_scan": 100,
        "rows_produced_per_join": 100,
        "filtered": "100.00",
        "using_index": true,
        "cost_info": {
          "read_cost": "3.75",
          "eval_cost": "10.00",
          "prefix_cost": "13.75",
          "data_read_per_join": "392K"
        },
        "used_columns": [
          "pk",
          "i1"
        ]
      }
    }
  }
}
Warnings:
Note	1003	/* select#1 */ select distinct `test`.`t1`.`i1` AS `i1` from `test`.`t1`
UPDATE mysql.server_cost
SET cost_value=DEFAULT;
#
# Test effect of changing memory_temptable_create_cost
#
# Use a query that creates a temporary table for a subquery.
# Run query with default cost constants.
#
EXPLAIN FORMAT=JSON SELECT * FROM t1
WHERE i1 IN (SELECT i1 FROM t1);
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "48.50"
    },
    "nested_loop": [
      {
        "table": {
          "table_name": "t1",
          "access_type": "ALL",
          "possible_keys": [
            "i1_key"
          ],
          "rows_examined_per_scan": 100,
          "rows_produced_per_join": 100,
          "filtered": "100.00",
          "cost_info": {
            "read_cost": "3.75",
            "eval_cost": "10.00",
            "prefix_cost": "13.75",
            "data_read_per_join": "392K"
          },
          "used_columns": [
            "pk",
            "i1",
            "c1",
            "c2",
            "c3",
            "c4"
          ],
          "attached_condition": "(`test`.`t1`.`i1` is not null)"
        }
      },
      {
        "table": {
          "table_name": "<subquery2>",
          "access_type": "eq_ref",
          "key": "<auto_distinct_key>",
          "key_length": "4",
          "ref": [
            "test.t1.i1"
          ],
          "rows_examined_per_scan": 1,
          "materialized_from_subquery": {
            "using_temporary_table": true,
            "query_block": {
              "table": {
                "table_name": "t1",
                "access_type": "index",
                "possible_keys": [
                  "i1_key"
                ],
                "key": "i1_key",
                "used_key_parts": [
                  "i1"
                ],
                "key_length": "4",
                "rows_examined_per_scan": 100,
                "rows_produced_per_join": 100,
                "filtered": "100.00",
                "using_index": true,
                "cost_info": {
                  "read_cost": "3.75",
                  "eval_cost": "10.00",
                  "prefix_cost": "13.75",
                  "data_read_per_join": "392K"
                },
                "used_columns": [
                  "i1"
                ]
              }
            }
          }
        }
      }
    ]
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1` semi join (`test`.`t1`) where (`<subquery2>`.`i1` = `test`.`t1`.`i1`)
UPDATE mysql.server_cost
SET cost_value=10.0
WHERE cost_name="memory_temptable_create_cost";
FLUSH OPTIMIZER_COSTS;
#
# Verify that the cost estimate for the query is incrased (by 9.0)
#
EXPLAIN FORMAT=JSON SELECT * FROM t1
WHERE i1 IN (SELECT i1 FROM t1);
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "57.50"
    },
    "nested_loop": [
      {
        "table": {
          "table_name": "t1",
          "access_type": "ALL",
          "possible_keys": [
            "i1_key"
          ],
          "rows_examined_per_scan": 100,
          "rows_produced_per_join": 100,
          "filtered": "100.00",
          "cost_info": {
            "read_cost": "3.75",
            "eval_cost": "10.00",
            "prefix_cost": "13.75",
            "data_read_per_join": "392K"
          },
          "used_columns": [
            "pk",
            "i1",
            "c1",
            "c2",
            "c3",
            "c4"
          ],
          "attached_condition": "(`test`.`t1`.`i1` is not null)"
        }
      },
      {
        "table": {
          "table_name": "<subquery2>",
          "access_type": "eq_ref",
          "key": "<auto_distinct_key>",
          "key_length": "4",
          "ref": [
            "test.t1.i1"
          ],
          "rows_examined_per_scan": 1,
          "materialized_from_subquery": {
            "using_temporary_table": true,
            "query_block": {
              "table": {
                "table_name": "t1",
                "access_type": "index",
                "possible_keys": [
                  "i1_key"
                ],
                "key": "i1_key",
                "used_key_parts": [
                  "i1"
                ],
                "key_length": "4",
                "rows_examined_per_scan": 100,
                "rows_produced_per_join": 100,
                "filtered": "100.00",
                "using_index": true,
                "cost_info": {
                  "read_cost": "3.75",
                  "eval_cost": "10.00",
                  "prefix_cost": "13.75",
                  "data_read_per_join": "392K"
                },
                "used_columns": [
                  "i1"
                ]
              }
            }
          }
        }
      }
    ]
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1` semi join (`test`.`t1`) where (`<subquery2>`.`i1` = `test`.`t1`.`i1`)
UPDATE mysql.server_cost
SET cost_value=DEFAULT;
#
# Test effect of changing memory_temptable_row_cost
#
# Use a query that creates a temporary table for a subquery.
# Result from running query with default cost constants:
#
EXPLAIN FORMAT=JSON SELECT * FROM t1
WHERE i1 IN (SELECT i1 FROM t1);
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "48.50"
    },
    "nested_loop": [
      {
        "table": {
          "table_name": "t1",
          "access_type": "ALL",
          "possible_keys": [
            "i1_key"
          ],
          "rows_examined_per_scan": 100,
          "rows_produced_per_join": 100,
          "filtered": "100.00",
          "cost_info": {
            "read_cost": "3.75",
            "eval_cost": "10.00",
            "prefix_cost": "13.75",
            "data_read_per_join": "392K"
          },
          "used_columns": [
            "pk",
            "i1",
            "c1",
            "c2",
            "c3",
            "c4"
          ],
          "attached_condition": "(`test`.`t1`.`i1` is not null)"
        }
      },
      {
        "table": {
          "table_name": "<subquery2>",
          "access_type": "eq_ref",
          "key": "<auto_distinct_key>",
          "key_length": "4",
          "ref": [
            "test.t1.i1"
          ],
          "rows_examined_per_scan": 1,
          "materialized_from_subquery": {
            "using_temporary_table": true,
            "query_block": {
              "table": {
                "table_name": "t1",
                "access_type": "index",
                "possible_keys": [
                  "i1_key"
                ],
                "key": "i1_key",
                "used_key_parts": [
                  "i1"
                ],
                "key_length": "4",
                "rows_examined_per_scan": 100,
                "rows_produced_per_join": 100,
                "filtered": "100.00",
                "using_index": true,
                "cost_info": {
                  "read_cost": "3.75",
                  "eval_cost": "10.00",
                  "prefix_cost": "13.75",
                  "data_read_per_join": "392K"
                },
                "used_columns": [
                  "i1"
                ]
              }
            }
          }
        }
      }
    ]
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1` semi join (`test`.`t1`) where (`<subquery2>`.`i1` = `test`.`t1`.`i1`)
UPDATE mysql.server_cost
SET cost_value=0.2
WHERE cost_name="memory_temptable_row_cost";
FLUSH OPTIMIZER_COSTS;
#
# Verify that the cost estimate for the query is incrased by:
# 100 rows that needs to be inserted and read from the temporary table.
# The cost of each insert and read is increased by 0.1, ie cost should
# be increased by 100 * 2 * 0.1 = 20.
#
EXPLAIN FORMAT=JSON SELECT * FROM t1
WHERE i1 IN (SELECT i1 FROM t1);
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "58.79"
    },
    "nested_loop": [
      {
        "table": {
          "table_name": "t1",
          "access_type": "ALL",
          "possible_keys": [
            "i1_key"
          ],
          "rows_examined_per_scan": 100,
          "rows_produced_per_join": 100,
          "filtered": "100.00",
          "cost_info": {
            "read_cost": "3.75",
            "eval_cost": "10.00",
            "prefix_cost": "13.75",
            "data_read_per_join": "392K"
          },
          "used_columns": [
            "pk",
            "i1",
            "c1",
            "c2",
            "c3",
            "c4"
          ]
        }
      },
      {
        "table": {
          "table_name": "t1",
          "access_type": "ref",
          "possible_keys": [
            "i1_key"
          ],
          "key": "i1_key",
          "used_key_parts": [
            "i1"
          ],
          "key_length": "4",
          "ref": [
            "test.t1.i1"
          ],
          "rows_examined_per_scan": 2,
          "rows_produced_per_join": 100,
          "filtered": "100.00",
          "using_index": true,
          "first_match": "t1",
          "cost_info": {
            "read_cost": "25.04",
            "eval_cost": "10.00",
            "prefix_cost": "58.79",
            "data_read_per_join": "392K"
          },
          "used_columns": [
            "i1"
          ]
        }
      }
    ]
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1` semi join (`test`.`t1`) where (`test`.`t1`.`i1` = `test`.`t1`.`i1`)
UPDATE mysql.server_cost
SET cost_value=DEFAULT;
set global internal_tmp_mem_storage_engine='memory';
set session internal_tmp_mem_storage_engine='memory';
set @max_heap_table_size_save= @@max_heap_table_size;
set max_heap_table_size= 16384;
#
# Test effect of changing disk_temptable_create_cost
#
# Use a query that creates a temporary table for a subquery.
# Result from running query with default cost constants:
#
EXPLAIN FORMAT=JSON SELECT * FROM t1
WHERE c1 IN (SELECT c1 FROM t1);
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "147.50"
    },
    "nested_loop": [
      {
        "table": {
          "table_name": "t1",
          "access_type": "ALL",
          "rows_examined_per_scan": 100,
          "rows_produced_per_join": 100,
          "filtered": "100.00",
          "cost_info": {
            "read_cost": "3.75",
            "eval_cost": "10.00",
            "prefix_cost": "13.75",
            "data_read_per_join": "392K"
          },
          "used_columns": [
            "pk",
            "i1",
            "c1",
            "c2",
            "c3",
            "c4"
          ],
          "attached_condition": "(`test`.`t1`.`c1` is not null)"
        }
      },
      {
        "table": {
          "table_name": "<subquery2>",
          "access_type": "eq_ref",
          "key": "<auto_distinct_key>",
          "key_length": "1001",
          "ref": [
            "test.t1.c1"
          ],
          "rows_examined_per_scan": 1,
          "materialized_from_subquery": {
            "using_temporary_table": true,
            "query_block": {
              "table": {
                "table_name": "t1",
                "access_type": "ALL",
                "rows_examined_per_scan": 100,
                "rows_produced_per_join": 100,
                "filtered": "100.00",
                "cost_info": {
                  "read_cost": "3.75",
                  "eval_cost": "10.00",
                  "prefix_cost": "13.75",
                  "data_read_per_join": "392K"
                },
                "used_columns": [
                  "c1"
                ]
              }
            }
          }
        }
      }
    ]
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1` semi join (`test`.`t1`) where (`<subquery2>`.`c1` = `test`.`t1`.`c1`)
UPDATE mysql.server_cost
SET cost_value=40.0
WHERE cost_name="disk_temptable_create_cost";
FLUSH OPTIMIZER_COSTS;
set max_heap_table_size= 16384;
#
# Verify that the cost estimate for the query is incrased (by 20.0)
#
EXPLAIN FORMAT=JSON SELECT * FROM t1
WHERE c1 IN (SELECT c1 FROM t1);
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "167.50"
    },
    "nested_loop": [
      {
        "table": {
          "table_name": "t1",
          "access_type": "ALL",
          "rows_examined_per_scan": 100,
          "rows_produced_per_join": 100,
          "filtered": "100.00",
          "cost_info": {
            "read_cost": "3.75",
            "eval_cost": "10.00",
            "prefix_cost": "13.75",
            "data_read_per_join": "392K"
          },
          "used_columns": [
            "pk",
            "i1",
            "c1",
            "c2",
            "c3",
            "c4"
          ],
          "attached_condition": "(`test`.`t1`.`c1` is not null)"
        }
      },
      {
        "table": {
          "table_name": "<subquery2>",
          "access_type": "eq_ref",
          "key": "<auto_distinct_key>",
          "key_length": "1001",
          "ref": [
            "test.t1.c1"
          ],
          "rows_examined_per_scan": 1,
          "materialized_from_subquery": {
            "using_temporary_table": true,
            "query_block": {
              "table": {
                "table_name": "t1",
                "access_type": "ALL",
                "rows_examined_per_scan": 100,
                "rows_produced_per_join": 100,
                "filtered": "100.00",
                "cost_info": {
                  "read_cost": "3.75",
                  "eval_cost": "10.00",
                  "prefix_cost": "13.75",
                  "data_read_per_join": "392K"
                },
                "used_columns": [
                  "c1"
                ]
              }
            }
          }
        }
      }
    ]
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1` semi join (`test`.`t1`) where (`<subquery2>`.`c1` = `test`.`t1`.`c1`)
UPDATE mysql.server_cost
SET cost_value=DEFAULT;
#
# Test effect of changing disk_temptable_row_cost
#
# Use a query that creates a temporary table for a subquery
# Result from running query with default cost constants:
#
EXPLAIN FORMAT=JSON SELECT * FROM t1
WHERE c1 IN (SELECT c1 FROM t1);
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "147.50"
    },
    "nested_loop": [
      {
        "table": {
          "table_name": "t1",
          "access_type": "ALL",
          "rows_examined_per_scan": 100,
          "rows_produced_per_join": 100,
          "filtered": "100.00",
          "cost_info": {
            "read_cost": "3.75",
            "eval_cost": "10.00",
            "prefix_cost": "13.75",
            "data_read_per_join": "392K"
          },
          "used_columns": [
            "pk",
            "i1",
            "c1",
            "c2",
            "c3",
            "c4"
          ],
          "attached_condition": "(`test`.`t1`.`c1` is not null)"
        }
      },
      {
        "table": {
          "table_name": "<subquery2>",
          "access_type": "eq_ref",
          "key": "<auto_distinct_key>",
          "key_length": "1001",
          "ref": [
            "test.t1.c1"
          ],
          "rows_examined_per_scan": 1,
          "materialized_from_subquery": {
            "using_temporary_table": true,
            "query_block": {
              "table": {
                "table_name": "t1",
                "access_type": "ALL",
                "rows_examined_per_scan": 100,
                "rows_produced_per_join": 100,
                "filtered": "100.00",
                "cost_info": {
                  "read_cost": "3.75",
                  "eval_cost": "10.00",
                  "prefix_cost": "13.75",
                  "data_read_per_join": "392K"
                },
                "used_columns": [
                  "c1"
                ]
              }
            }
          }
        }
      }
    ]
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1` semi join (`test`.`t1`) where (`<subquery2>`.`c1` = `test`.`t1`.`c1`)
UPDATE mysql.server_cost
SET cost_value=1.0
WHERE cost_name="disk_temptable_row_cost";
FLUSH OPTIMIZER_COSTS;
set max_heap_table_size= 16384;
#
# Verify that the cost estimate for the query is incrased by:
# 100 rows that needs to be inserted and read from the temporary table.
# The cost of each insert and read is increased by 0.5, ie cost should
# be increased by 100 * 2 * 0.5 = 100.
#
EXPLAIN FORMAT=JSON SELECT * FROM t1
WHERE c1 IN (SELECT c1 FROM t1);
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "247.50"
    },
    "nested_loop": [
      {
        "table": {
          "table_name": "t1",
          "access_type": "ALL",
          "rows_examined_per_scan": 100,
          "rows_produced_per_join": 100,
          "filtered": "100.00",
          "cost_info": {
            "read_cost": "3.75",
            "eval_cost": "10.00",
            "prefix_cost": "13.75",
            "data_read_per_join": "392K"
          },
          "used_columns": [
            "pk",
            "i1",
            "c1",
            "c2",
            "c3",
            "c4"
          ],
          "attached_condition": "(`test`.`t1`.`c1` is not null)"
        }
      },
      {
        "table": {
          "table_name": "<subquery2>",
          "access_type": "eq_ref",
          "key": "<auto_distinct_key>",
          "key_length": "1001",
          "ref": [
            "test.t1.c1"
          ],
          "rows_examined_per_scan": 1,
          "materialized_from_subquery": {
            "using_temporary_table": true,
            "query_block": {
              "table": {
                "table_name": "t1",
                "access_type": "ALL",
                "rows_examined_per_scan": 100,
                "rows_produced_per_join": 100,
                "filtered": "100.00",
                "cost_info": {
                  "read_cost": "3.75",
                  "eval_cost": "10.00",
                  "prefix_cost": "13.75",
                  "data_read_per_join": "392K"
                },
                "used_columns": [
                  "c1"
                ]
              }
            }
          }
        }
      }
    ]
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1` semi join (`test`.`t1`) where (`<subquery2>`.`c1` = `test`.`t1`.`c1`)
UPDATE mysql.server_cost
SET cost_value=DEFAULT;
set max_heap_table_size= @max_heap_table_size_save;
set session internal_tmp_mem_storage_engine=default;
set global internal_tmp_mem_storage_engine=default;
#
# Test effect of changing the memory_block_read_cost
#
# Result from running query with default cost constants:
#
EXPLAIN FORMAT=JSON SELECT * FROM t1;
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "13.75"
    },
    "table": {
      "table_name": "t1",
      "access_type": "ALL",
      "rows_examined_per_scan": 100,
      "rows_produced_per_join": 100,
      "filtered": "100.00",
      "cost_info": {
        "read_cost": "3.75",
        "eval_cost": "10.00",
        "prefix_cost": "13.75",
        "data_read_per_join": "392K"
      },
      "used_columns": [
        "pk",
        "i1",
        "c1",
        "c2",
        "c3",
        "c4"
      ]
    }
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1`
UPDATE mysql.engine_cost
SET cost_value=0.5
WHERE cost_name="memory_block_read_cost";
FLUSH OPTIMIZER_COSTS;
#
# Verify that the cost estimate for read cost has doubled
#
EXPLAIN FORMAT=JSON SELECT * FROM t1;
EXPLAIN
{
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "17.50"
    },
    "table": {
      "table_name": "t1",
      "access_type": "ALL",
      "rows_examined_per_scan": 100,
      "rows_produced_per_join": 100,
      "filtered": "100.00",
      "cost_info": {
        "read_cost": "7.50",
        "eval_cost": "10.00",
        "prefix_cost": "17.50",
        "data_read_per_join": "392K"
      },
      "used_columns": [
        "pk",
        "i1",
        "c1",
        "c2",
        "c3",
        "c4"
      ]
    }
  }
}
Warnings:
Note	1003	/* select#1 */ select `test`.`t1`.`pk` AS `pk`,`test`.`t1`.`i1` AS `i1`,`test`.`t1`.`c1` AS `c1`,`test`.`t1`.`c2` AS `c2`,`test`.`t1`.`c3` AS `c3`,`test`.`t1`.`c4` AS `c4` from `test`.`t1`
UPDATE mysql.engine_cost
SET cost_value=DEFAULT;
FLUSH OPTIMIZER_COSTS;
DROP TABLE t0,t1;