You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Bo Jin (JIRA)" <ji...@apache.org> on 2015/12/16 05:44:46 UTC
[jira] [Updated] (SPARK-12353) wrong output for countByValue and
countByValueAndWindow
[ https://issues.apache.org/jira/browse/SPARK-12353?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Bo Jin updated SPARK-12353:
---------------------------
Description:
http://stackoverflow.com/q/34114585/4698425
In PySpark Streaming, function countByValue and countByValueAndWindow return one single number which is the count of distinct elements, instead of a list of (k,v) pairs.
It's inconsistent with the documentation:
countByValue: When called on a DStream of elements of type K, return a new DStream of (K, Long) pairs where the value of each key is its frequency in each RDD of the source DStream.
countByValueAndWindow: When called on a DStream of (K, V) pairs, returns a new DStream of (K, Long) pairs where the value of each key is its frequency within a sliding window. Like in reduceByKeyAndWindow, the number of reduce tasks is configurable through an optional argument.
was:
http://stackoverflow.com/q/34114585/4698425
Function countByValue and countByValueAndWindow return one single number which is the count of distinct elements, instead of a list of (k,v) pairs.
It's inconsistent with the documentation:
countByValue: When called on a DStream of elements of type K, return a new DStream of (K, Long) pairs where the value of each key is its frequency in each RDD of the source DStream.
countByValueAndWindow: When called on a DStream of (K, V) pairs, returns a new DStream of (K, Long) pairs where the value of each key is its frequency within a sliding window. Like in reduceByKeyAndWindow, the number of reduce tasks is configurable through an optional argument.
> wrong output for countByValue and countByValueAndWindow
> -------------------------------------------------------
>
> Key: SPARK-12353
> URL: https://issues.apache.org/jira/browse/SPARK-12353
> Project: Spark
> Issue Type: Bug
> Components: Documentation, Input/Output, PySpark, Streaming
> Affects Versions: 1.5.2
> Environment: Ubuntu 14.04, Python 2.7.6
> Reporter: Bo Jin
> Labels: easyfix
> Original Estimate: 2h
> Remaining Estimate: 2h
>
> http://stackoverflow.com/q/34114585/4698425
> In PySpark Streaming, function countByValue and countByValueAndWindow return one single number which is the count of distinct elements, instead of a list of (k,v) pairs.
> It's inconsistent with the documentation:
> countByValue: When called on a DStream of elements of type K, return a new DStream of (K, Long) pairs where the value of each key is its frequency in each RDD of the source DStream.
> countByValueAndWindow: When called on a DStream of (K, V) pairs, returns a new DStream of (K, Long) pairs where the value of each key is its frequency within a sliding window. Like in reduceByKeyAndWindow, the number of reduce tasks is configurable through an optional argument.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org