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[SPARK-20194] Add support for partition pruning to in-memory catalog #17510
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Original file line number | Diff line number | Diff line change |
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@@ -18,6 +18,7 @@ | |
package org.apache.spark.sql.catalyst.catalog | ||
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import java.net.URI | ||
import java.util.TimeZone | ||
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import org.apache.hadoop.conf.Configuration | ||
import org.apache.hadoop.fs.Path | ||
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@@ -28,6 +29,7 @@ import org.apache.spark.sql.AnalysisException | |
import org.apache.spark.sql.catalyst.{FunctionIdentifier, TableIdentifier} | ||
import org.apache.spark.sql.catalyst.analysis.{FunctionAlreadyExistsException, NoSuchDatabaseException, NoSuchFunctionException} | ||
import org.apache.spark.sql.catalyst.analysis.TableAlreadyExistsException | ||
import org.apache.spark.sql.catalyst.expressions._ | ||
import org.apache.spark.sql.types._ | ||
import org.apache.spark.util.Utils | ||
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@@ -436,6 +438,37 @@ abstract class ExternalCatalogSuite extends SparkFunSuite with BeforeAndAfterEac | |
assert(catalog.listPartitions("db2", "tbl2", Some(Map("a" -> "unknown"))).isEmpty) | ||
} | ||
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test("list partitions by filter") { | ||
val tz = TimeZone.getDefault().getID() | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Nit: |
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val catalog = newBasicCatalog() | ||
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def checkAnswer(table: CatalogTable, filters: Seq[Expression], | ||
expected: Set[CatalogTablePartition]): Unit = { | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. nit: code style
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assertResult(expected.map(_.spec)) { | ||
catalog.listPartitionsByFilter(table.database, table.identifier.identifier, filters, tz) | ||
.map(_.spec).toSet | ||
} | ||
} | ||
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def pcol(table: CatalogTable, name: String): Expression = { | ||
val col = table.partitionSchema(name) | ||
AttributeReference(col.name, col.dataType, col.nullable)() | ||
} | ||
val tbl2 = catalog.getTable("db2", "tbl2") | ||
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checkAnswer(tbl2, Seq.empty, Set(part1, part2)) | ||
checkAnswer(tbl2, Seq(EqualTo(pcol(tbl2, "a"), Literal(1))), Set(part1)) | ||
checkAnswer(tbl2, Seq(EqualTo(pcol(tbl2, "a"), Literal(2))), Set.empty) | ||
checkAnswer(tbl2, Seq(In(pcol(tbl2, "a"), Seq(Literal(3)))), Set(part2)) | ||
checkAnswer(tbl2, Seq(Not(In(pcol(tbl2, "a"), Seq(Literal(4))))), Set(part1, part2)) | ||
checkAnswer(tbl2, Seq( | ||
EqualTo(pcol(tbl2, "a"), Literal(1)), | ||
EqualTo(pcol(tbl2, "b"), Literal("2"))), Set(part1)) | ||
checkAnswer(tbl2, Seq( | ||
EqualTo(pcol(tbl2, "a"), Literal(1)), | ||
EqualTo(pcol(tbl2, "b"), Literal("x"))), Set.empty) | ||
} | ||
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test("drop partitions") { | ||
val catalog = newBasicCatalog() | ||
assert(catalogPartitionsEqual(catalog, "db2", "tbl2", Seq(part1, part2))) | ||
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@@ -35,7 +35,7 @@ import org.apache.spark.sql.AnalysisException | |
import org.apache.spark.sql.catalyst.TableIdentifier | ||
import org.apache.spark.sql.catalyst.analysis.TableAlreadyExistsException | ||
import org.apache.spark.sql.catalyst.catalog._ | ||
import org.apache.spark.sql.catalyst.catalog.ExternalCatalogUtils.escapePathName | ||
import org.apache.spark.sql.catalyst.catalog.ExternalCatalogUtils._ | ||
import org.apache.spark.sql.catalyst.expressions._ | ||
import org.apache.spark.sql.catalyst.plans.logical.ColumnStat | ||
import org.apache.spark.sql.catalyst.util.CaseInsensitiveMap | ||
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@@ -1039,37 +1039,14 @@ private[spark] class HiveExternalCatalog(conf: SparkConf, hadoopConf: Configurat | |
defaultTimeZoneId: String): Seq[CatalogTablePartition] = withClient { | ||
val rawTable = getRawTable(db, table) | ||
val catalogTable = restoreTableMetadata(rawTable) | ||
val partitionColumnNames = catalogTable.partitionColumnNames.toSet | ||
val nonPartitionPruningPredicates = predicates.filterNot { | ||
_.references.map(_.name).toSet.subsetOf(partitionColumnNames) | ||
} | ||
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if (nonPartitionPruningPredicates.nonEmpty) { | ||
sys.error("Expected only partition pruning predicates: " + | ||
predicates.reduceLeft(And)) | ||
} | ||
val partColNameMap = buildLowerCasePartColNameMap(catalogTable) | ||
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val partitionSchema = catalogTable.partitionSchema | ||
val partColNameMap = buildLowerCasePartColNameMap(getTable(db, table)) | ||
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if (predicates.nonEmpty) { | ||
val clientPrunedPartitions = client.getPartitionsByFilter(rawTable, predicates).map { part => | ||
val clientPrunedPartitions = | ||
client.getPartitionsByFilter(rawTable, predicates).map { part => | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. if There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. A similar optimization is done in the function itself: client.getPartitionsByFilter(), while Hive Shim_v0_12 delegates to I've now made the only piece of non-trivial code along that path lazy, so I think we're good. |
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part.copy(spec = restorePartitionSpec(part.spec, partColNameMap)) | ||
} | ||
val boundPredicate = | ||
InterpretedPredicate.create(predicates.reduce(And).transform { | ||
case att: AttributeReference => | ||
val index = partitionSchema.indexWhere(_.name == att.name) | ||
BoundReference(index, partitionSchema(index).dataType, nullable = true) | ||
}) | ||
clientPrunedPartitions.filter { p => | ||
boundPredicate(p.toRow(partitionSchema, defaultTimeZoneId)) | ||
} | ||
} else { | ||
client.getPartitions(catalogTable).map { part => | ||
part.copy(spec = restorePartitionSpec(part.spec, partColNameMap)) | ||
} | ||
} | ||
prunePartitionsByFilter(catalogTable, clientPrunedPartitions, predicates, defaultTimeZoneId) | ||
} | ||
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// -------------------------------------------------------------------------- | ||
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Nit: Throwing an
AnalysisException
is preferred.There was a problem hiding this comment.
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Could you add the negative test cases in your newly added test cases?