EXPLAIN 语句

    Java

    可以使用 的 executeSql() 方法执行 EXPLAIN 语句。如果 EXPLAIN 操作执行成功，executeSql() 方法会返回解释结果，否则会抛出异常。

    以下示例展示了如何在 TableEnvironment 中执行一条 EXPLAIN 语句。

    Scala

    可以使用 TableEnvironment 的 executeSql() 方法执行 EXPLAIN 语句。如果 EXPLAIN 操作执行成功，executeSql() 方法会返回解释结果，否则会抛出异常。

    以下示例展示了如何在 TableEnvironment 中执行一条 EXPLAIN 语句。

    可以使用 TableEnvironment 的 execute_sql() 方法执行 EXPLAIN 语句。如果 EXPLAIN 操作执行成功，execute_sql() 方法会返回解释结果，否则会抛出异常。

    以下示例展示了如何在 TableEnvironment 中执行一条 EXPLAIN 语句。

    SQL CLI

    EXPLAIN 语句可以在 SQL CLI 中执行。

    以下示例展示了如何在 SQL CLI 中执行一条 EXPLAIN 语句。

    Java

    1. val env = StreamExecutionEnvironment.getExecutionEnvironment()
    2. val tEnv = StreamTableEnvironment.create(env)
    4. // 注册名为 “Orders” 的表
    5. tEnv.executeSql("CREATE TABLE MyTable1 (`count` bigint, word VARCHAR(256)) WITH ('connector' = 'datagen')")
    6. tEnv.executeSql("CREATE TABLE MyTable2 (`count` bigint, word VARCHAR(256)) WITH ('connector' = 'datagen')")
    8. // 调用 TableEnvironment.explainSql() 来解释 SELECT 语句
    9. val explanation = tEnv.explainSql(
    10.   "SELECT `count`, word FROM MyTable1 WHERE word LIKE 'F%' " +
    11.   "UNION ALL " + 
    12.   "SELECT `count`, word FROM MyTable2")
    13. println(explanation)
    15. // 调用 TableEnvironment.executeSql() 来解释 SELECT 语句
    16. val tableResult = tEnv.executeSql(
    17.   "EXPLAIN PLAN FOR " + 
    18.   "SELECT `count`, word FROM MyTable1 WHERE word LIKE 'F%' " +
    19.   "UNION ALL " + 
    20.   "SELECT `count`, word FROM MyTable2")
    21. tableResult.print()
    23. val tableResult2 = tEnv.executeSql(
    24.   "EXPLAIN ESTIMATED_COST, CHANGELOG_MODE, JSON_EXECUTION_PLAN " + 
    26.   "UNION ALL " + 
    27.   "SELECT `count`, word FROM MyTable2")
    28. tableResult2.print()

    Python

    SQL CLI

    1. Flink SQL> CREATE TABLE MyTable1 (`count` bigint, word VARCHAR(256)) WITH ('connector' = 'datagen');
    3. Flink SQL> CREATE TABLE MyTable2 (`count` bigint, word VARCHAR(256)) WITH ('connector' = 'datagen');
    4. [INFO] Table has been created.
    6. Flink SQL> EXPLAIN PLAN FOR SELECT `count`, word FROM MyTable1 WHERE word LIKE 'F%' 
    7. > UNION ALL 
    8. > SELECT `count`, word FROM MyTable2;
    10. Flink SQL> EXPLAIN ESTIMATED_COST, CHANGELOG_MODE, JSON_EXECUTION_PLAN SELECT `count`, word FROM MyTable1 
    11. > WHERE word LIKE 'F%' 
    12. > UNION ALL 
    13. > SELECT `count`, word FROM MyTable2;

    EXPLAIN 的结果如下:

    EXPLAIN PLAN

    EXPLAIN PLAN WITH DETAILS

    1. == Abstract Syntax Tree ==
    2. LogicalUnion(all=[true])
    3. :- LogicalProject(count=[$0], word=[$1])
    4. :  +- LogicalFilter(condition=[LIKE($1, _UTF-16LE'F%')])
    5. :     +- LogicalTableScan(table=[[default_catalog, default_database, MyTable1]])
    6. +- LogicalProject(count=[$0], word=[$1])
    7.    +- LogicalTableScan(table=[[default_catalog, default_database, MyTable2]])
    9. == Optimized Physical Plan ==
    10. Union(all=[true], union=[count, word], changelogMode=[I]): rowcount = 1.05E8, cumulative cost = {3.1E8 rows, 3.05E8 cpu, 4.0E9 io, 0.0 network, 0.0 memory}
    11. :- Calc(select=[count, word], where=[LIKE(word, _UTF-16LE'F%')], changelogMode=[I]): rowcount = 5000000.0, cumulative cost = {1.05E8 rows, 1.0E8 cpu, 2.0E9 io, 0.0 network, 0.0 memory}
    12. :  +- TableSourceScan(table=[[default_catalog, default_database, MyTable1]], fields=[count, word], changelogMode=[I]): rowcount = 1.0E8, cumulative cost = {1.0E8 rows, 1.0E8 cpu, 2.0E9 io, 0.0 network, 0.0 memory}
    13. +- TableSourceScan(table=[[default_catalog, default_database, MyTable2]], fields=[count, word], changelogMode=[I]): rowcount = 1.0E8, cumulative cost = {1.0E8 rows, 1.0E8 cpu, 2.0E9 io, 0.0 network, 0.0 memory}
    15. == Optimized Execution Plan ==
    16. Union(all=[true], union=[count, word])
    17. :- Calc(select=[count, word], where=[LIKE(word, _UTF-16LE'F%')])
    19. +- TableSourceScan(table=[[default_catalog, default_database, MyTable2]], fields=[count, word])
    21. {
    22.   "nodes" : [ {
    23.     "id" : 37,
    24.     "type" : "Source: TableSourceScan(table=[[default_catalog, default_database, MyTable1]], fields=[count, word])",
    25.     "pact" : "Data Source",
    26.     "contents" : "Source: TableSourceScan(table=[[default_catalog, default_database, MyTable1]], fields=[count, word])",
    27.     "parallelism" : 1
    28.   }, {
    29.     "id" : 38,
    30.     "type" : "Calc(select=[count, word], where=[LIKE(word, _UTF-16LE'F%')])",
    31.     "pact" : "Operator",
    32.     "contents" : "Calc(select=[count, word], where=[LIKE(word, _UTF-16LE'F%')])",
    33.     "parallelism" : 1,
    34.     "predecessors" : [ {
    35.       "id" : 37,
    36.       "ship_strategy" : "FORWARD",
    37.       "side" : "second"
    38.     } ]
    39.   }, {
    40.     "id" : 39,
    41.     "type" : "Source: TableSourceScan(table=[[default_catalog, default_database, MyTable2]], fields=[count, word])",
    42.     "pact" : "Data Source",
    43.     "contents" : "Source: TableSourceScan(table=[[default_catalog, default_database, MyTable2]], fields=[count, word])",
    44.     "parallelism" : 1
    45.   } ]
    1. EXPLAIN [([ExplainDetail[, ExplainDetail]*]) | PLAN FOR] <query_statement_or_insert_statement_or_statement_set>
    3. statement_set:
    4. EXECUTE STATEMENT SET
    5. BEGIN
    6. insert_statement;
    7. ...
    8. END;

    关于 query 的语法，请查阅 页面。 关于 INSERT 的语法，请查阅 INSERT 页面。