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Thanks very much
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GitHub user wangtao605 opened a pull request:
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[SPARK-24803] add support for numeric
numerical is as same with decimal. Spark has already supported
decimalï¼so i think we should add support for numeric to align SQL standards.
You
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sgtm
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--- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
@@ -2336,6 +2336,18 @@ class SparkContext(config: SparkConf) extends
Logging {
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--- Diff: R/pkg/R/context.R ---
@@ -435,3 +435,31 @@ setCheckpointDir <- function(directory) {
sc <- getSparkContext()
Github user cloud-fan commented on the issue:
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OK we can treat it as a data loss. However, it's not caused by spark but by
the user himself. If a user calls `zip` and then using a custom function to
compute keys from the zipped pairs, and
Github user HyukjinKwon commented on the issue:
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Ah, I am happy too that it's added back. Was just simply wondering if I can
fix the fix version in SPARK-12850 JIRA. Nothing more then this. Thank you
@cloud-fan.
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+/*
+ * Licensed to the Apache
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package
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Github user cloud-fan commented on the issue:
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IIUC the bucket pruning was accidentally removed during refactoring, I'm
happy to see it's added back.
The migration must keep all the existing features. I think we have enough
tests to
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cc @gatorsmile @cloud-fan @gengliangwang @michal-databricks
@mswit-databricks
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Yeah let's merge this - think there might be some work to clean this up a
bit later.
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Ok documentation is done, this is fully ready for review now.
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[MINOR][CORE] Add test cases for RDD.cartesian
## What changes were proposed in this pull request?
While looking through the codebase, it appeared that the scala code for
RDD.cartesian
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Ok, integration test is green. Probably should add some docs though -
following up in a moment.
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[SPARK-24802] Optimization Rule Exclusion
## What changes were proposed in this pull request?
Since Spark has provided fairly clear interfaces for adding user-defined
optimization
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LGTM
Thanks! Merged to master
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@mccheah
@foxish
Can we merge?
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@madanadit can you close this as #21260 has been merged?
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Integration test isn't ready for review but the main code is.
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@mccheah Is this ready for review?
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Github user MaxGekk commented on the issue:
https://github.com/apache/spark/pull/21589
> in this cluster do we really mean cores allocated to the "application" or
"job"?
@felixcheung What about `number of CPUs/Executors potentially available to
an job submitted via the
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