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SortExec Unary Physical Operator

SortExec is a unary physical operator (that, among other use cases, represents Sort logical operators at execution).

Creating Instance

SortExec takes the following to be created:

SortExec is created when:

Performance Metrics

Key Name (in web UI) Description
peakMemory peak memory
sortTime sort time
spillSize spill size

Radix Sort

SortExec operator uses the spark.sql.sort.enableRadixSort configuration property when creating an UnsafeExternalRowSorter.


SortExec is a BlockingOperatorWithCodegen.


SortExec supports Java code generation (indirectly as a BlockingOperatorWithCodegen).

Output Data Ordering Requirements

outputOrdering: Seq[SortOrder]

outputOrdering is the given SortOrder expressions.

outputOrdering is part of the SparkPlan abstraction.

Required Child Output Distribution

requiredChildDistribution: Seq[Distribution]

requiredChildDistribution is a OrderedDistribution (with the SortOrder expressions) with the global flag enabled or a UnspecifiedDistribution.

requiredChildDistribution is part of the SparkPlan abstraction.

Physical Optimizations


OptimizeSkewedJoin physical optimization is used to optimize skewed SortMergeJoinExecs (with SortExec operators) in Adaptive Query Execution.


SortExec operators can be removed from a physical query plan by RemoveRedundantSorts physical optimization (with spark.sql.execution.removeRedundantSorts enabled).

Creating UnsafeExternalRowSorter

createSorter(): UnsafeExternalRowSorter


createSorter is used when:


val q = Seq((0, "zero"), (1, "one")).toDF("id", "name").sort('id)
val qe = q.queryExecution

val logicalPlan = qe.analyzed
scala> println(logicalPlan.numberedTreeString)
00 Sort [id#72 ASC NULLS FIRST], true
01 +- Project [_1#69 AS id#72, _2#70 AS name#73]
02    +- LocalRelation [_1#69, _2#70]

// BasicOperators does the conversion of Sort logical operator to SortExec
val sparkPlan = qe.sparkPlan
scala> println(sparkPlan.numberedTreeString)
00 Sort [id#72 ASC NULLS FIRST], true, 0
01 +- LocalTableScan [id#72, name#73]

// SortExec supports Whole-Stage Code Generation
val executedPlan = qe.executedPlan
scala> println(executedPlan.numberedTreeString)
00 *(1) Sort [id#72 ASC NULLS FIRST], true, 0
01 +- Exchange rangepartitioning(id#72 ASC NULLS FIRST, 200)
02    +- LocalTableScan [id#72, name#73]

import org.apache.spark.sql.execution.SortExec
val sortExec = executedPlan.collect { case se: SortExec => se }.head
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