Github user chhao01 commented on a diff in the pull request:
https://github.com/apache/spark/pull/8023#discussion_r37488201
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/CacheManager.scala ---
@@ -156,10 +165,27 @@ private[sql] class CacheManager(sqlContext:
SQLContext) extends Logging {
* function will over invalidate.
*/
private[sql] def invalidateCache(plan: LogicalPlan): Unit = writeLock {
- cachedData.foreach {
- case data if data.plan.collect { case p if p.sameResult(plan) => p
}.nonEmpty =>
- data.cachedRepresentation.recache()
- case _ =>
+ var i = 0
+ var locatedIdx = -1
+ // find the index of the cached data, according to the specified
logical plan
+ while (i < cachedData.length && locatedIdx < 0) {
+ cachedData(i) match {
+ case data if data.plan.collect { case p if p.sameResult(plan) => p
}.nonEmpty =>
+ locatedIdx = i
+ case _ =>
+ }
+ i += 1
+ }
+
+ if (locatedIdx >= 0) {
+ // if the cached data exists, remove it from the cache data list, as
we need to
+ // re-generate the spark plan, and we don't want the this to be used
during the
+ // re-generation
+ val entry = cachedData.remove(locatedIdx) // TODO do we have to use
ArrayBuffer?
+ // rebuild the cache
+ entry.recache(sqlContext)
+ // add it back to the cache data list
+ cachedData += entry
--- End diff --
And probably we can not simply use the `data.plan.find`, as the cached data
most likely will add wrapper like `LogicalPlan` etc.
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