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org.apache.spark.sql.execution.bucketing

DisableUnnecessaryBucketedScan

object DisableUnnecessaryBucketedScan extends Rule[SparkPlan]

Disable unnecessary bucketed table scan based on actual physical query plan. NOTE: this rule is designed to be applied right after EnsureRequirements, where all ShuffleExchangeExec and SortExec have been added to plan properly.

When BUCKETING_ENABLED and AUTO_BUCKETED_SCAN_ENABLED are set to true, go through query plan to check where bucketed table scan is unnecessary, and disable bucketed table scan if:

1. The sub-plan from root to bucketed table scan, does not contain hasInterestingPartition operator.

2. The sub-plan from the nearest downstream hasInterestingPartition operator to the bucketed table scan, contains only isAllowedUnaryExecNode operators and at least one Exchange.

Examples: 1. no hasInterestingPartition operator: Project | Filter | Scan(t1: i, j) (bucketed on column j, DISABLE bucketed scan)

2. join: SortMergeJoin(t1.i = t2.j) / \ Sort(i) Sort(j) / \ Shuffle(i) Scan(t2: i, j) / (bucketed on column j, enable bucketed scan) Scan(t1: i, j) (bucketed on column j, DISABLE bucketed scan)

3. aggregate: HashAggregate(i, ..., Final) | Shuffle(i) | HashAggregate(i, ..., Partial) | Filter | Scan(t1: i, j) (bucketed on column j, DISABLE bucketed scan)

The idea of hasInterestingPartition is inspired from "interesting order" in the paper "Access Path Selection in a Relational Database Management System" (https://dl.acm.org/doi/10.1145/582095.582099).

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Rule[SparkPlan], Logging, SQLConfHelper, AnyRef, Any
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