0 配置

Table 和 SQL API 的默认配置能够确保结果准确，同时也提供可接受的性能。

根据 Table 程序的需求，可能需要调整特定的参数用于优化。例如，无界流程序可能需要保证所需的状态是有限的(请参阅 ​​流式概念​​).

1 概览

在每个 TableEnvironment 中，​​TableConfig​​ 提供用于当前会话的配置项。

对于常见或者重要的配置项，​​TableConfig​​ 提供带有详细注释的 ​​getters​​ 和 ​​setters​​ 方法。

对于更加高级的配置，用户可以直接访问底层的 key-value 配置项。以下章节列举了所有可用于调整 Flink Table 和 SQL API 程序的配置项。

注意 因为配置项会在执行操作的不同时间点被读取，所以推荐在实例化 TableEnvironment 后尽早地设置配置项。



// instantiate table environment
val tEnv: TableEnvironment = ...

// access flink configuration
val configuration = tEnv.getConfig().getConfiguration()
// set low-level key-value options
configuration.setString("table.exec.mini-batch.enabled", "true")
configuration.setString("table.exec.mini-batch.allow-latency", "5 s")
configuration.setString("table.exec.mini-batch.size", "5000")


注意 目前，key-value 配置项仅被 Blink planner 支持。

2 执行配置

以下选项可用于优化查询执行的性能。

 

Key

Default

Type

Description


table.exec.async-lookup.buffer-capacity


Batch Streaming

100

Integer

The max number of async i/o operation that the async lookup join can trigger.


table.exec.async-lookup.timeout


Batch Streaming

"3 min"

String

The async timeout for the asynchronous operation to complete.


table.exec.disabled-operators


Batch

(none)

String

Mainly for testing. A comma-separated list of operator names, each name represents a kind of disabled operator. Operators that can be disabled include "NestedLoopJoin", "ShuffleHashJoin", "BroadcastHashJoin", "SortMergeJoin", "HashAgg", "SortAgg". By default no operator is disabled.


table.exec.mini-batch.allow-latency


Streaming

"-1 ms"

String

The maximum latency can be used for MiniBatch to buffer input records. MiniBatch is an optimization to buffer input records to reduce state access. MiniBatch is triggered with the allowed latency interval and when the maximum number of buffered records reached. NOTE: If table.exec.mini-batch.enabled is set true, its value must be greater than zero.


table.exec.mini-batch.enabled


Streaming

false

Boolean

Specifies whether to enable MiniBatch optimization. MiniBatch is an optimization to buffer input records to reduce state access. This is disabled by default. To enable this, users should set this config to true. NOTE: If mini-batch is enabled, 'table.exec.mini-batch.allow-latency' and 'table.exec.mini-batch.size' must be set.


table.exec.mini-batch.size


Streaming

-1

Long

The maximum number of input records can be buffered for MiniBatch. MiniBatch is an optimization to buffer input records to reduce state access. MiniBatch is triggered with the allowed latency interval and when the maximum number of buffered records reached. NOTE: MiniBatch only works for non-windowed aggregations currently. If table.exec.mini-batch.enabled is set true, its value must be positive.


table.exec.resource.default-parallelism


Batch Streaming

-1

Integer

Sets default parallelism for all operators (such as aggregate, join, filter) to run with parallel instances. This config has a higher priority than parallelism of StreamExecutionEnvironment (actually, this config overrides the parallelism of StreamExecutionEnvironment). A value of -1 indicates that no default parallelism is set, then it will fallback to use the parallelism of StreamExecutionEnvironment.


table.exec.shuffle-mode


Batch

"ALL_EDGES_BLOCKING"

String

Sets exec shuffle mode.

Accepted values are:

  • ALL_EDGES_BLOCKING
    : All edges will use blocking shuffle.
  • FORWARD_EDGES_PIPELINED
    : Forward edges will use pipelined shuffle, others blocking.
  • POINTWISE_EDGES_PIPELINED
    : Pointwise edges will use pipelined shuffle, others blocking. Pointwise edges include forward and rescale edges.
  • ALL_EDGES_PIPELINED
    : All edges will use pipelined shuffle.
  • batch
    : the same as ALL_EDGES_BLOCKING
    . Deprecated.
  • pipelined
    : the same as ALL_EDGES_PIPELINED
    . Deprecated.

              Note: Blocking shuffle means data will be fully produced before sent to consumer tasks. Pipelined shuffle means data will be sent to consumer tasks once produced.


              table.exec.sink.not-null-enforcer


              Batch Streaming

              ERROR


              Enum

              Possible values: [ERROR, DROP]

              The NOT NULL column constraint on a table enforces that null values can't be inserted into the table. Flink supports 'error' (default) and 'drop' enforcement behavior. By default, Flink will check values and throw runtime exception when null values writing into NOT NULL columns. Users can change the behavior to 'drop' to silently drop such records without throwing exception.


              table.exec.sort.async-merge-enabled


              Batch

              true

              Boolean

              Whether to asynchronously merge sorted spill files.


              table.exec.sort.default-limit


              Batch

              -1

              Integer

              Default limit when user don't set a limit after order by. -1 indicates that this configuration is ignored.


              table.exec.sort.max-num-file-handles


              Batch

              128

              Integer

              The maximal fan-in for external merge sort. It limits the number of file handles per operator. If it is too small, may cause intermediate merging. But if it is too large, it will cause too many files opened at the same time, consume memory and lead to random reading.


              table.exec.source.idle-timeout


              Streaming

              "-1 ms"

              String

              When a source do not receive any elements for the timeout time, it will be marked as temporarily idle. This allows downstream tasks to advance their watermarks without the need to wait for watermarks from this source while it is idle.


              table.exec.spill-compression.block-size


              Batch

              "64 kb"

              String

              The memory size used to do compress when spilling data. The larger the memory, the higher the compression ratio, but more memory resource will be consumed by the job.


              table.exec.spill-compression.enabled


              Batch

              true

              Boolean

              Whether to compress spilled data. Currently we only support compress spilled data for sort and hash-agg and hash-join operators.


              table.exec.window-agg.buffer-size-limit


              Batch

              100000

              Integer

              Sets the window elements buffer size limit used in group window agg operator.

               

              3 优化器配置

              以下配置可以用于调整查询优化器的行为以获得更好的执行计划。

               

              Key

              Default

              Type

              Description


              table.optimizer.agg-phase-strategy


              Batch Streaming

              "AUTO"

              String

              Strategy for aggregate phase. Only AUTO, TWO_PHASE or ONE_PHASE can be set. AUTO: No special enforcer for aggregate stage. Whether to choose two stage aggregate or one stage aggregate depends on cost. TWO_PHASE: Enforce to use two stage aggregate which has localAggregate and globalAggregate. Note that if aggregate call does not support optimize into two phase, we will still use one stage aggregate. ONE_PHASE: Enforce to use one stage aggregate which only has CompleteGlobalAggregate.


              table.optimizer.distinct-agg.split.bucket-num


              Streaming

              1024

              Integer

              Configure the number of buckets when splitting distinct aggregation. The number is used in the first level aggregation to calculate a bucket key 'hash_code(distinct_key) % BUCKET_NUM' which is used as an additional group key after splitting.


              table.optimizer.distinct-agg.split.enabled


              Streaming

              false

              Boolean

              Tells the optimizer whether to split distinct aggregation (e.g. COUNT(DISTINCT col), SUM(DISTINCT col)) into two level. The first aggregation is shuffled by an additional key which is calculated using the hashcode of distinct_key and number of buckets. This optimization is very useful when there is data skew in distinct aggregation and gives the ability to scale-up the job. Default is false.


              table.optimizer.join-reorder-enabled


              Batch Streaming

              false

              Boolean

              Enables join reorder in optimizer. Default is disabled.


              table.optimizer.join.broadcast-threshold


              Batch

              1048576

              Long

              Configures the maximum size in bytes for a table that will be broadcast to all worker nodes when performing a join. By setting this value to -1 to disable broadcasting.


              table.optimizer.reuse-source-enabled


              Batch Streaming

              true

              Boolean

              When it is true, the optimizer will try to find out duplicated table sources and reuse them. This works only when table.optimizer.reuse-sub-plan-enabled is true.


              table.optimizer.reuse-sub-plan-enabled


              Batch Streaming

              true

              Boolean

              When it is true, the optimizer will try to find out duplicated sub-plans and reuse them.


              table.optimizer.source.predicate-pushdown-enabled


              Batch Streaming

              true

              Boolean

              When it is true, the optimizer will push down predicates into the FilterableTableSource. Default value is true.

               

              4 Planner 配置

              以下配置可以用于调整 planner 的行为。


              Key

              Default

              Type

              Description


              table.dynamic-table-options.enabled


              Batch Streaming

              false

              Boolean

              Enable or disable the OPTIONS hint used to specify table optionsdynamically, if disabled, an exception would be thrown if any OPTIONS hint is specified


              table.sql-dialect


              Batch Streaming

              "default"

              String

              The SQL dialect defines how to parse a SQL query. A different SQL dialect may support different SQL grammar. Currently supported dialects are: default and hive