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AnalyzeTableCommand Logical Command

AnalyzeTableCommand is a RunnableCommand.md[logical command] that <> (i.e. <> and <>) for a <> and stores the stats in a metastore.

AnalyzeTableCommand is <> exclusively for spark-sql-SparkSqlAstBuilder.md#AnalyzeTableCommand[ANALYZE TABLE] with no PARTITION specification and FOR COLUMNS clause.

[source, scala]

// Seq((0, 0, "zero"), (1, 1, "one")).toDF("id", "p1", "p2").write.partitionBy("p1", "p2").saveAsTable("t1") val sqlText = "ANALYZE TABLE t1 COMPUTE STATISTICS NOSCAN" val plan = spark.sql(sqlText).queryExecution.logical import org.apache.spark.sql.execution.command.AnalyzeTableCommand val cmd = plan.asInstanceOf[AnalyzeTableCommand] scala> println(cmd) AnalyzeTableCommand t1, false

=== [[run]] Executing Logical Command (Computing Table-Level Statistics and Altering Metastore) -- run Method

[source, scala]

run(sparkSession: SparkSession): Seq[Row]

NOTE: run is part of <> to execute (run) a logical command.

run requests the session-specific SessionCatalog for the metadata of the <> and makes sure that it is not a view (aka temporary table).

NOTE: run uses the input SparkSession to access the session-specific SparkSession.md#sessionState[SessionState] that in turn gives access to the current SessionState.md#catalog[SessionCatalog].

[[total-size-stat]][[row-count-stat]] run computes the total size and, without <> flag, the row count statistics of the table.

NOTE: run uses SparkSession to SparkSession.md#table[find the table] in a metastore.

In the end, run alters table statistics if different from the existing table statistics in metastore.

run throws a AnalysisException when executed on a view.

ANALYZE TABLE is not supported on views.

[NOTE]

Row count statistics triggers a Spark job to count the number of rows in a table (that happens with ANALYZE TABLE with no NOSCAN flag).

[source, scala]

// Seq((0, 0, "zero"), (1, 1, "one")).toDF("id", "p1", "p2").write.partitionBy("p1", "p2").saveAsTable("t1") val sqlText = "ANALYZE TABLE t1 COMPUTE STATISTICS" val plan = spark.sql(sqlText).queryExecution.logical import org.apache.spark.sql.execution.command.AnalyzeTableCommand val cmd = plan.asInstanceOf[AnalyzeTableCommand] scala> println(cmd) AnalyzeTableCommand t1, false

// Execute ANALYZE TABLE // Check out web UI's Jobs tab for the number of Spark jobs // http://localhost:4040/jobs/ spark.sql(sqlText).show

====

=== [[creating-instance]] Creating AnalyzeTableCommand Instance

AnalyzeTableCommand takes the following when created:

  • [[tableIdent]] TableIdentifier
  • [[noscan]] noscan flag (enabled by default) that indicates whether spark-sql-cost-based-optimization.md#NOSCAN[NOSCAN] option was used or not
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