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--- Diff: python/pyspark/sql/readwriter.py ---
@@ -747,16 +800,25 @@ def _test():
except py4j.protocol.Py4JError:
spark =
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LGTM
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Github user hvanhovell commented on the issue:
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Merging to master. Thanks!
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--- Diff:
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@@ -0,0 +1,102 @@
+/*
+ * Licensed to the
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@@ -79,8 +79,16 @@ object FileSourceStrategy
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@@ -184,7 +184,7 @@ case class FileSourceScanExec(
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+/*
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala ---
@@ -2531,6 +2531,8 @@ class Dataset[T] private[sql](
*/
def inputFiles:
Github user davies commented on the issue:
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Merged this into master and 2.0 branch, thanks!
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Merging this into master and 2.0 branch, thanks!
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@davies Fine, thx.
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Github user vanzin commented on the issue:
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The issue I see is how easy is it for the driver to know that? Adding a new
flag to the `SlaveLost` class doesn't mean that you know how to set its value.
I'm pretty sure, on the YARN side,
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cc @felixcheung
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Looks fine.
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LGTM
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@@ -62,8 +68,39 @@ class JacksonParser(
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Github user davies commented on the issue:
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@heroldus decodeDictionaryIds() is only used when a batch across pages with
different encoding (dictionary or plain), so it's not in the hot pass, I think
the performance impact should be fine.
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@sameeragarwal: Do you expect any performace impact of this commit? It's an
additional `if (!column.isNullAt(i))` for every single value read.
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LGTM, pending jenkins.
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GitHub user junyangq opened a pull request:
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[SparkR][Minor] Fix docs for sparkR.session and count
## What changes were proposed in this pull request?
This PR tries to add some more explanation to `sparkR.session`. It also
modifies
Github user davies commented on the issue:
https://github.com/apache/spark/pull/12436
@sitalkedia Have a quick look at this one, the use case sounds good, we
should improve the stability for long running tasks. Could you explain a bit
more how the current patch works? (in the PR
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[SPARK-16334] Reusing same dictionary column for decoding consecutive row
groups shouldn't throw an error
## What changes were proposed in this pull request?
This patch fixes a bug
Github user zsxwing commented on the issue:
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I just checkpicked this one into branch 1.6
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Github user JoshRosen commented on the issue:
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I'm actually going to close this now and will revisit later; the scheduling
complexity may not be warranted now given benefits of simpler approaches.
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Github user hvanhovell commented on the issue:
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I just compared the wide schema benchmark on master with this patch and
there do not seem to be performance regressions.
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Github user JoshRosen commented on the issue:
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@davies brought up a reasonable point that we might be able to achieve
similar benefits with less complexity by replacing the exponential ramp-up with
something that's linearly proportional to
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Can one of the admins verify this patch?
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Github user srinathshankar commented on the issue:
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I'll update the python and R APIs in a follow up. Right now in python and R
a cross join is done if no join exprs/columns and join types are specified. It
would be good to require explicit
GitHub user bookling opened a pull request:
https://github.com/apache/spark/pull/14940
[SPARK-17383][GRAPHX]LabelPropagation
In the labelPropagation of graphx lib, node is initialized with a unique
label and at every step each node adopts the label that most of its
neighbors
Github user ericl commented on the issue:
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What if we added a flag to SlaveLost indicating if we think the entire host
is lost? In many cases that should be true, if the event originated from worker
loss or Mesos slave loss events.
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--- Diff:
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@@ -479,13 +480,23 @@ case class DataSource(
Github user shivaram commented on the issue:
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Ah thanks - I didn't notice this while merging the earlier PR.
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