{"action":"created","comment":{"url":"https://api.github.com/repos/apache/spark/pulls/comments/81259064","pull_request_review_id":2252545,"id":81259064,"diff_hunk":"@@ -32,19 +38,84 @@ package org.apache.spark.sql.catalyst.plans.logical\n  * @param sizeInBytes Physical size in bytes. For leaf operators this defaults to 1, otherwise it\n  *                    defaults to the product of children's `sizeInBytes`.\n  * @param rowCount Estimated number of rows.\n+ * @param colStats Column-level statistics.\n  * @param isBroadcastable If true, output is small enough to be used in a broadcast join.\n  */\n case class Statistics(\n     sizeInBytes: BigInt,\n     rowCount: Option[BigInt] = None,\n+    colStats: Map[String, ColumnStat] = Map.empty,\n     isBroadcastable: Boolean = false) {\n+\n   override def toString: String = \"Statistics(\" + simpleString + \")\"\n \n   /** Readable string representation for the Statistics. */\n   def simpleString: String = {\n     Seq(s\"sizeInBytes=$sizeInBytes\",\n       if (rowCount.isDefined) s\"rowCount=${rowCount.get}\" else \"\",\n       s\"isBroadcastable=$isBroadcastable\"\n-    ).filter(_.nonEmpty).mkString(\"\", \", \", \"\")\n+    ).filter(_.nonEmpty).mkString(\", \")\n+  }\n+}\n+\n+/**\n+ * Statistics for a column.\n+ */\n+case class ColumnStat(statRow: InternalRow) {\n+\n+  def forNumeric[T <: AtomicType](dataType: T): NumericColumnStat[T] = {\n+    NumericColumnStat(statRow, dataType)\n+  }\n+  def forString: StringColumnStat = StringColumnStat(statRow)\n+  def forBinary: BinaryColumnStat = BinaryColumnStat(statRow)\n+  def forBoolean: BooleanColumnStat = BooleanColumnStat(statRow)\n+\n+  override def toString: String = {\n+    // use Base64 for encoding\n+    Base64.encodeBase64String(statRow.asInstanceOf[UnsafeRow].getBytes)\n   }\n }\n+\n+object ColumnStat {\n+  def apply(dataType: DataType, str: String): ColumnStat = {\n+    // use Base64 for decoding\n+    val bytes = Base64.decodeBase64(str)\n+    val numFields = dataType match {\n+      case BinaryType | BooleanType => 3\n+      case _ => 4\n+    }\n+    val unsafeRow = new UnsafeRow(numFields)","path":"sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/Statistics.scala","position":null,"original_position":64,"commit_id":"3335af65c2b53dcfa96bf1f5602043cf3d11e3b1","original_commit_id":"1d3dd621531185e34fc5ad91e7e85337009ab286","user":{"login":"cloud-fan","id":3182036,"avatar_url":"https://avatars.githubusercontent.com/u/3182036?v=3","gravatar_id":"","url":"https://api.github.com/users/cloud-fan","html_url":"https://github.com/cloud-fan","followers_url":"https://api.github.com/users/cloud-fan/followers","following_url":"https://api.github.com/users/cloud-fan/following{/other_user}","gists_url":"https://api.github.com/users/cloud-fan/gists{/gist_id}","starred_url":"https://api.github.com/users/cloud-fan/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/cloud-fan/subscriptions","organizations_url":"https://api.github.com/users/cloud-fan/orgs","repos_url":"https://api.github.com/users/cloud-fan/repos","events_url":"https://api.github.com/users/cloud-fan/events{/privacy}","received_events_url":"https://api.github.com/users/cloud-fan/received_events","type":"User","site_admin":false},"body":"ah i see, sorry I read the code wrong","created_at":"2016-09-30T00:00:05Z","updated_at":"2016-09-30T00:00:05Z","html_url":"https://github.com/apache/spark/pull/15090#discussion_r81259064","pull_request_url":"https://api.github.com/repos/apache/spark/pulls/15090","_links":{"self":{"href":"https://api.github.com/repos/apache/spark/pulls/comments/81259064"},"html":{"href":"https://github.com/apache/spark/pull/15090#discussion_r81259064"},"pull_request":{"href":"https://api.github.com/repos/apache/spark/pulls/15090"}}},"pull_request":{"url":"https://api.github.com/repos/apache/spark/pulls/15090","id":85163180,"html_url":"https://github.com/apache/spark/pull/15090","diff_url":"https://github.com/apache/spark/pull/15090.diff","patch_url":"https://github.com/apache/spark/pull/15090.patch","issue_url":"https://api.github.com/repos/apache/spark/issues/15090","number":15090,"state":"open","locked":false,"title":"[SPARK-17073] [SQL] generate column-level statistics","user":{"login":"wzhfy","id":10878553,"avatar_url":"https://avatars.githubusercontent.com/u/10878553?v=3","gravatar_id":"","url":"https://api.github.com/users/wzhfy","html_url":"https://github.com/wzhfy","followers_url":"https://api.github.com/users/wzhfy/followers","following_url":"https://api.github.com/users/wzhfy/following{/other_user}","gists_url":"https://api.github.com/users/wzhfy/gists{/gist_id}","starred_url":"https://api.github.com/users/wzhfy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/wzhfy/subscriptions","organizations_url":"https://api.github.com/users/wzhfy/orgs","repos_url":"https://api.github.com/users/wzhfy/repos","events_url":"https://api.github.com/users/wzhfy/events{/privacy}","received_events_url":"https://api.github.com/users/wzhfy/received_events","type":"User","site_admin":false},"body":"## What changes were proposed in this pull request?\r\n\r\nGenerate basic column statistics for all the atomic types:\r\n- numeric types: max, min, num of nulls, ndv (number of distinct values)\r\n- date/timestamp types: they are also represented as numbers internally, so they have the same stats as above.\r\n- string: avg length, max length, num of nulls, ndv\r\n- binary: avg length, max length, num of nulls\r\n- boolean: num of nulls, num of trues, num of falsies\r\n\r\nAlso support storing and loading these statistics.\r\n\r\nOne thing to notice:\r\nWe support analyzing columns independently, e.g.:\r\nsql1: `ANALYZE TABLE src COMPUTE STATISTICS FOR COLUMNS key;`\r\nsql2: `ANALYZE TABLE src COMPUTE STATISTICS FOR COLUMNS value;`\r\nwhen running sql2 to collect column stats for `value`, we don’t remove stats of columns `key` which are analyzed in sql1 and not in sql2. As a result, **users need to guarantee consistency** between sql1 and sql2. If the table has been changed before sql2, users should re-analyze column `key` when they want to analyze column `value`:\r\n`ANALYZE TABLE src COMPUTE STATISTICS FOR COLUMNS key, value;`\r\n\r\n## How was this patch tested?\r\n\r\nadd unit 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