SaintBacchus created SPARK-6605: ----------------------------------- Summary: Same transformation in DStream leads to different result Key: SPARK-6605 URL: https://issues.apache.org/jira/browse/SPARK-6605 Project: Spark Issue Type: Bug Components: Streaming Affects Versions: 1.3.0 Reporter: SaintBacchus Fix For: 1.4.0
The transformation *reduceByKeyAndWindow* has two implementations: one use the *WindowDstream* and the other use *ReducedWindowedDStream*. But the result always is the same, except when an empty windows occurs. As a wordcount example, if a period of time (larger than window time) has no data coming, the first *reduceByKeyAndWindow* has no elem inside but the second has many elem with the zero value inside. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org