Github user hvanhovell commented on a diff in the pull request:
https://github.com/apache/spark/pull/14712#discussion_r75502235
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/command/AnalyzeTableCommand.scala
---
@@ -33,7 +34,7 @@ import
org.apache.spark.sql.catalyst.catalog.{CatalogRelation, CatalogTable}
* Right now, it only supports Hive tables and it only updates the size of
a Hive table
* in the Hive metastore.
*/
-case class AnalyzeTableCommand(tableName: String) extends RunnableCommand {
+case class AnalyzeTableCommand(tableName: String, noscan: Boolean = true)
extends RunnableCommand {
--- End diff --
Collecting statistics has a cost, so you would normally do this every once
in a while, and not on every change to your data. The underlying idea is that
the distribution of data typically doesn't change to much.
If we were to store the input statistics aggregation buffers somewhere, you
could actually update statistics easily after an insert (you only need to scan
the inserted data).
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