Github user mbasmanova commented on a diff in the pull request:
https://github.com/apache/spark/pull/18421#discussion_r130408151
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/command/AnalyzePartitionCommand.scala
---
@@ -0,0 +1,149 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.command
+
+import org.apache.spark.sql.{AnalysisException, Column, Row, SparkSession}
+import org.apache.spark.sql.catalyst.TableIdentifier
+import org.apache.spark.sql.catalyst.analysis.{NoSuchPartitionException,
UnresolvedAttribute}
+import org.apache.spark.sql.catalyst.catalog.{CatalogTable,
CatalogTableType}
+import
org.apache.spark.sql.catalyst.catalog.CatalogTypes.TablePartitionSpec
+import org.apache.spark.sql.catalyst.expressions.{And, EqualTo, Literal}
+
+/**
+ * Analyzes a given set of partitions to generate per-partition
statistics, which will be used in
+ * query optimizations.
+ *
+ * When `partitionSpec` is empty, statistics for all partitions are
collected and stored in
+ * Metastore.
+ *
+ * When `partitionSpec` mentions only some of the partition columns, all
partitions with
+ * matching values for specified columns are processed.
+ *
+ * If `partitionSpec` mentions unknown partition column, an
`AnalysisException` is raised.
+ *
+ * By default, total number of rows and total size in bytes is calculated.
When `noscan`
+ * is `false`, only total size in bytes is computed.
+ */
+case class AnalyzePartitionCommand(
+ tableIdent: TableIdentifier,
+ partitionSpec: Map[String, Option[String]],
+ noscan: Boolean = true) extends RunnableCommand {
+
+ private def validatePartitionSpec(table: CatalogTable):
Option[TablePartitionSpec] = {
+ val partitionColumnNames = table.partitionColumnNames.toSet
+ val invalidColumnNames =
partitionSpec.keys.filterNot(partitionColumnNames.contains(_))
+ if (invalidColumnNames.nonEmpty) {
+ val tableId = table.identifier
+ throw new AnalysisException(s"Partition specification for table
'${tableId.table}' " +
+ s"in database '${tableId.database}' refers to unknown partition
column(s): " +
+ invalidColumnNames.mkString(","))
+ }
+
+ val filteredSpec = partitionSpec.filter(_._2.isDefined)
+ if (filteredSpec.isEmpty) {
+ None
+ } else {
+ Some(filteredSpec.mapValues(_.get))
+ }
+ }
+
+ override def run(sparkSession: SparkSession): Seq[Row] = {
+ val sessionState = sparkSession.sessionState
+ val db =
tableIdent.database.getOrElse(sessionState.catalog.getCurrentDatabase)
+ val tableIdentWithDB = TableIdentifier(tableIdent.table, Some(db))
+ val tableMeta = sessionState.catalog.getTableMetadata(tableIdentWithDB)
+ if (tableMeta.tableType == CatalogTableType.VIEW) {
+ throw new AnalysisException("ANALYZE TABLE is not supported on
views.")
+ }
+
+ val partitionValueSpec = validatePartitionSpec(tableMeta)
+
+ val partitions =
sessionState.catalog.listPartitions(tableMeta.identifier, partitionValueSpec)
+
+ if (partitions.isEmpty) {
+ if (partitionValueSpec.isDefined) {
+ throw new NoSuchPartitionException(db, tableIdent.table,
partitionValueSpec.get)
+ } else {
+ // the user requested to analyze all partitions for a table which
has no partitions
+ // return normally, since there is nothing to do
+ return Seq.empty[Row]
+ }
+ }
+
+ // Compute statistics for individual partitions
+ val rowCounts: Map[TablePartitionSpec, BigInt] =
+ if (noscan) {
+ Map.empty
+ } else {
+ calculateRowCountsPerPartition(sparkSession, tableMeta,
partitionValueSpec)
+ }
+
+ // Update the metastore if newly computed statistics are different
from those
+ // recorded in the metastore.
+ val partitionStats = partitions.map { p =>
+ val newTotalSize = CommandUtils.calculateLocationSize(sessionState,
+ tableMeta.identifier, p.storage.locationUri)
+ val newRowCount = rowCounts.get(p.spec)
+ val newStats = CommandUtils.compareAndGetNewStats(tableMeta.stats,
newTotalSize, newRowCount)
+ (p, newStats)
+ }
+
+ val newPartitions = partitionStats.filter(_._2.isDefined).map { case
(p, newStats) =>
+ p.copy(stats = newStats)
+ }.toList
+
+ if (newPartitions.nonEmpty) {
+ sessionState.catalog.alterPartitions(tableMeta.identifier,
newPartitions)
+ }
+
+ Seq.empty[Row]
+ }
+
+ private def calculateRowCountsPerPartition(
+ sparkSession: SparkSession,
+ tableMeta: CatalogTable,
+ partitionValueSpec: Option[TablePartitionSpec]):
Map[TablePartitionSpec, BigInt] = {
+ val filter = if (partitionValueSpec.isDefined) {
+ val filters = partitionValueSpec.get.map {
+ case (columnName, value) =>
EqualTo(UnresolvedAttribute(columnName), Literal(value))
+ }
+ Some(filters.reduce(And))
+ } else {
+ None
--- End diff --
@gatorsmile , I don't understand this comment. Do you want me to change
None to Literal.TrueLiteral? This doesn't compile and doesn't make sense to me
as Literal.TrueLiteral just represents 'true' which is not a valid filter.
Could you explain a little bit?
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