org.apache.spark.sql.execution
GenerateExec
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package execution
the generator expression
when true, each output row is implicitly joined with the input tuple that produced it.
when true, each input row will be output at least once, even if the output of the
given generator is empty. outer has no effect when join is false.
the qualified output attributes of the generator of this node, which constructed in analysis phase, and we can not change it, as the parent node bound with it already.
Eagerly clear any broadcasts created by this plan execution.
Eagerly clear any broadcasts created by this plan execution.
Overridden by concrete implementations of SparkPlan.
Overridden by concrete implementations of SparkPlan. Produces the result of the query as an RDD[InternalRow]
Overridden by concrete implementations of SparkPlan.
Overridden by concrete implementations of SparkPlan. Produces the result of the query as a broadcast variable.
Overridden by concrete implementations of SparkPlan.
Overridden by concrete implementations of SparkPlan. It is guaranteed to run before any
execute of SparkPlan. This is helpful if we want to set up some state before executing the
query, e.g., BroadcastHashJoin uses it to broadcast asynchronously.
Note: the prepare method has already walked down the tree, so the implementation doesn't need to call children's prepare methods.
This will only be called once, protected by this.
Returns the result of this query as an RDD[InternalRow] by delegating to doExecute after
preparations.
Returns the result of this query as an RDD[InternalRow] by delegating to doExecute after
preparations.
Concrete implementations of SparkPlan should override doExecute.
Returns the result of this query as a broadcast variable by delegating to doExecuteBroadcast
after preparations.
Returns the result of this query as a broadcast variable by delegating to doExecuteBroadcast
after preparations.
Concrete implementations of SparkPlan should override doExecuteBroadcast.
Runs this query returning the result as an array.
Runs this query returning the result as an array.
Runs this query returning the result as an array, using external Row format.
Runs this query returning the result as an array, using external Row format.
Execute a query after preparing the query and adding query plan information to created RDDs for visualization.
Execute a query after preparing the query and adding query plan information to created RDDs for visualization.
Runs this query returning the first n rows as an array.
Runs this query returning the first n rows as an array.
This is modeled after RDD.take but never runs any job locally on the driver.
Runs this query returning the result as an iterator of InternalRow.
Runs this query returning the result as an iterator of InternalRow.
Note: this will trigger multiple jobs (one for each partition).
the generator expression
the qualified output attributes of the generator of this node, which constructed in analysis phase, and we can not change it, as the parent node bound with it already.
when true, each output row is implicitly joined with the input tuple that produced it.
Return a LongSQLMetric according to the name.
Return a LongSQLMetric according to the name.
Overridden make copy also propagates sqlContext to copied plan.
Overridden make copy also propagates sqlContext to copied plan.
Return all metadata that describes more details of this SparkPlan.
Return all metadata that describes more details of this SparkPlan.
Return all metrics containing metrics of this SparkPlan.
Return all metrics containing metrics of this SparkPlan.
Creates a row ordering for the given schema, in natural ascending order.
Creates a row ordering for the given schema, in natural ascending order.
when true, each input row will be output at least once, even if the output of the
given generator is empty.
when true, each input row will be output at least once, even if the output of the
given generator is empty. outer has no effect when join is false.
Specifies how data is ordered in each partition.
Specifies how data is ordered in each partition.
Specifies how data is partitioned across different nodes in the cluster.
Specifies how data is partitioned across different nodes in the cluster.
Prepare a SparkPlan for execution.
Prepare a SparkPlan for execution. It's idempotent.
Finds scalar subquery expressions in this plan node and starts evaluating them.
Finds scalar subquery expressions in this plan node and starts evaluating them.
Specifies any partition requirements on the input data for this operator.
Specifies any partition requirements on the input data for this operator.
Specifies sort order for each partition requirements on the input data for this operator.
Specifies sort order for each partition requirements on the input data for this operator.
Reset all the metrics.
Reset all the metrics.
A handle to the SQL Context that was used to create this plan.
A handle to the SQL Context that was used to create this plan. Since many operators need access to the sqlContext for RDD operations or configuration this field is automatically populated by the query planning infrastructure.
Blocks the thread until all subqueries finish evaluation and update the results.
Blocks the thread until all subqueries finish evaluation and update the results.
Applies a Generator to a stream of input rows, combining the output of each into a new stream of rows. This operation is similar to a
flatMapin functional programming with one important additional feature, which allows the input rows to be joined with their output.the generator expression
when true, each output row is implicitly joined with the input tuple that produced it.
when true, each input row will be output at least once, even if the output of the given
generatoris empty.outerhas no effect whenjoinis false.the qualified output attributes of the generator of this node, which constructed in analysis phase, and we can not change it, as the parent node bound with it already.