Github user davies commented on the pull request:
https://github.com/apache/spark/pull/1812#issuecomment-51402466
cc @mateiz
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/1791#issuecomment-51402751
@JoshRosen @mateiz Could you take a look at this? I hope that this can be
in 1.1.
---
If your project is set up for it, you can reply to this email and have your
reply
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/1791#discussion_r15907204
--- Diff: python/pyspark/context.py ---
@@ -727,6 +738,13 @@ def sparkUser(self):
return self._jsc.sc().sparkUser
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/1791#issuecomment-51405218
The difference is that whether those unimplemented API should in the API
docs, I think we should have an complete set of API in Java or Python, and user
can easily know
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/1791#discussion_r15916433
--- Diff: python/pyspark/context.py ---
@@ -727,6 +738,13 @@ def sparkUser(self):
return self._jsc.sc().sparkUser
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/1791#discussion_r15955661
--- Diff: python/pyspark/rdd.py ---
@@ -737,6 +754,19 @@ def _collect_iterator_through_file(self, iterator):
yield item
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/1842
[SPARK-2898] [PySpark] fix bugs in deamon.py
1. do not use signal handler for SIGCHILD, it's easy to cause deadlock
2. handle EINTR during accept()
3. pass errno into JVM
4. handle EAGAIN
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/1776#issuecomment-51543727
Before moving on, maybe the first question is that, does Spark 1.1 is so
stable that we can trust it work as expected? If yes in most cases, I think
reduce the chatty
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/1894
[SPARK-2790] [PySPark] fix zip with serializers which have different batch
sizes.
If two RDDs have different batch size in serializers, then it will try to
re-serialize the one with smaller batch
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/1791#discussion_r16072784
--- Diff: core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
---
@@ -741,6 +741,23 @@ private[spark] object PythonRDD extends Logging
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/1791#issuecomment-51826195
@JoshRosen @mateiz I had commented out those not implemented APIs.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub
Github user davies closed the pull request at:
https://github.com/apache/spark/pull/1791
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature
GitHub user davies reopened a pull request:
https://github.com/apache/spark/pull/1791
[SPARK-2871] [PySpark] Add missing API
Try to bring all Java/Scala API to PySpark.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/davies/spark
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/1791#issuecomment-51826337
closed by accident
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/1894#issuecomment-51829030
The failure is not related to this PR, how to re-test this?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/1898
[SPARK-705] [PySpark] improve performance of sortByKey()
1. skip partitionBy() when numOfPartition is 1
2. use bisect_left (O(lg(N))) instread of loop (O(N)) in
rangePartitioner
You can
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/1910
fix flaky tests
Python 2.6 does not handle float error well as 2.7+
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/davies/spark fix_test
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/1912
[SPARK-1065] [PySpark] improve supporting for large broadcast
Passing large object by py4j is very slow (cost much memory), so pass
broadcast objects via files (similar to parallelize
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/1912#issuecomment-52001814
failed tests were not related to this PR
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2538#discussion_r18557162
--- Diff: python/pyspark/streaming/tests.py ---
@@ -0,0 +1,548 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2538#discussion_r18557210
--- Diff: python/pyspark/streaming/context.py ---
@@ -0,0 +1,319 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2538#issuecomment-58282175
@tdas It looks like the tests are stable enough, it had 5 successes in a
row.
---
If your project is set up for it, you can reply to this email and have your
reply
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2538#issuecomment-58284518
I had created an JIRA to track the hacks for py4j:
https://issues.apache.org/jira/browse/SPARK-3842
---
If your project is set up for it, you can reply to this email
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2563#issuecomment-58307821
@marmbrus I think this is ready to go.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2716
[SPARK-3594] [PySpark] [SQL] take more rows to infer schema or sampling
This patch will try to infer schema for RDD which has empty value (None,
[], {}) in the first row. It will try first 100 rows
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2717#issuecomment-58436504
It's reproducable by this query:
```
SELECT strlen(a) FROM test WHERE strlen(a) 1
```
---
If your project is set up for it, you can reply to this email
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2717#issuecomment-58438988
@marmbrus Could you add a test in pyhon/pyspark/tests.py (SQLTests) ?
---
If your project is set up for it, you can reply to this email and have your
reply appear
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2716#issuecomment-58440322
@nchammas This PR only fix the problem of having empty values in first few
rows, it can not handle different types for one field (like what json() had
done
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2651#issuecomment-58445558
LGTM, thanks!
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2659#issuecomment-58445706
The code in the JIRA could be used for test this.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2724#issuecomment-58456661
LGTM.
Jenkins, test this please.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2717#discussion_r18687839
--- Diff: python/pyspark/tests.py ---
@@ -679,6 +679,12 @@ def test_udf(self):
[row] = self.sqlCtx.sql(SELECT twoArgs('test', 1)).collect
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2538#issuecomment-58691755
@giwa No, it's under testing/QA
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2717#issuecomment-58710443
@marmbrus LGTM, just wonder that why you do not use IntegerType as
returnType in the tests? (no change needed)
---
If your project is set up for it, you can reply
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2538#issuecomment-58739136
@tdas The failure looked wired, updater() take exactly two arguments, let's
test it again.
---
If your project is set up for it, you can reply to this email and have
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2538#issuecomment-58739234
@tdas it's my mistake, the updateStateByKey() was used in another tests,
it's fixed now.
---
If your project is set up for it, you can reply to this email and have your
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2648#issuecomment-58925491
@yingjieMiao it looks good to me, waiting for other people.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2806
[SPARK-3916] [Streaming] discover new appended data for fileStream()
In a case that new data will be appended to existed files continuously,
then fileStream() should discovery the new appended data
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2681#issuecomment-59120483
Sometimes hit this bug during pyspark testing
```
Py4JJavaError: An error occurred while calling o55.collect. :
org.apache.spark.SparkException: Job aborted due
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2808
[SPARK-3952] add Python examples in Streaming Programming Guide
Having Python examples in Streaming Programming Guide.
Also add RecoverableNetworkWordCount example.
You can merge this pull
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2819
[SPARK-3961] Python API for mllib.feature
Added completed Python API for MLlib.feature
Normalizer
StandardScalerModel
StandardScaler
HashTF
IDFModel
IDF
You can merge
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2819#discussion_r18932968
--- Diff: python/pyspark/mllib/feature.py ---
@@ -95,90 +360,46 @@ class Word2Vec(object):
sentence = a b * 100 + a c * 10
localDoc
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2830
[SPARK-3971] [MLLib] [PySpark] hotfix: Customized pickler should work in
cluster mode
Customized pickler should be registered before unpickling, but in executor,
there is no way to register
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2830#issuecomment-59430263
@mengxr @falaki it had passed all the tests, the last two commits are just
refactor, I think it's ready to merge.
---
If your project is set up for it, you can reply
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2830#issuecomment-59437296
@mengxr The failed case is not related.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project
Github user davies closed the pull request at:
https://github.com/apache/spark/pull/2830
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2833
[SPARK-3982] [Streaming] [PySpark] Python API: receiverStream()
This patch brings receiverStream() for Python API, it could be used to
create an input stream with any arbitrary user implemented
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2681#issuecomment-59464471
This error was not happened in tests of this PR, it happened in tests of
our product, which have similar pattern as streaming, the job was submitted via
py4j
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2808#discussion_r19001885
--- Diff: docs/streaming-programming-guide.md ---
@@ -398,6 +498,30 @@ JavaSparkContext sc = ... //existing JavaSparkContext
JavaStreamingContext ssc
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2808#issuecomment-59469000
@JoshRosen I had addressed your comments, also added code tabs for design
patterns section.
---
If your project is set up for it, you can reply to this email and have
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2838
[SPARK-3993] [PySpark] fix bug while reuse worker after take()
After take(), maybe there are some garbage left in the socket, then next
task assigned to this worker will hang because of corrupted
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2808#issuecomment-59576834
@JoshRosen fixed.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2806#issuecomment-59578404
@tdas Could you help to review this? The failed tests run stable locally,
I'm investigating it.
---
If your project is set up for it, you can reply to this email
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2743#discussion_r19051269
--- Diff: python/pyspark/conf.py ---
@@ -57,6 +57,22 @@
__all__ = ['SparkConf']
+def _parse_memory(s):
+
+Parse a memory
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2743#discussion_r19051286
--- Diff: core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
---
@@ -63,9 +64,12 @@ private[spark] class PythonRDD(
val localdir
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2838#issuecomment-59596407
@aarondav Yes, before reuse workers, every python task will fork a new
python worker.
---
If your project is set up for it, you can reply to this email and have your
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2681#issuecomment-59634598
I hope that we can have this in 1.1, some people see regression in 1.1
because of TorrentBroadcast, this patch will help for those.
---
If your project is set up
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2838#discussion_r19057007
--- Diff: python/pyspark/worker.py ---
@@ -57,7 +57,7 @@ def main(infile, outfile):
boot_time = time.time()
split_index = read_int
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2838#issuecomment-59635035
take() is not the only one which will introduce problems, user could call
mapPartitions(), and read parts of the items in the infile.
Not only re-use the worker
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2808#issuecomment-59635066
@JoshRosen updated the readme.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2844#discussion_r19063222
--- Diff:
core/src/main/scala/org/apache/spark/broadcast/TorrentBroadcast.scala ---
@@ -76,23 +87,20 @@ private[spark] class TorrentBroadcast[T: ClassTag
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2844#discussion_r19063253
--- Diff:
core/src/main/scala/org/apache/spark/broadcast/TorrentBroadcast.scala ---
@@ -62,6 +59,20 @@ private[spark] class TorrentBroadcast[T: ClassTag
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2844#discussion_r19063271
--- Diff:
core/src/main/scala/org/apache/spark/broadcast/TorrentBroadcast.scala ---
@@ -156,6 +158,7 @@ private[spark] class TorrentBroadcast[T: ClassTag
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2844#discussion_r19063455
--- Diff:
core/src/main/scala/org/apache/spark/broadcast/TorrentBroadcast.scala ---
@@ -179,43 +183,29 @@ private[spark] class TorrentBroadcast[T: ClassTag
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2743#discussion_r19066507
--- Diff: core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
---
@@ -63,9 +64,12 @@ private[spark] class PythonRDD(
val localdir
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2844#issuecomment-59803868
LGTM now, thanks!
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2870
[SPARK-4023] [MLlib] [PySpark] convert rdd into RDD of Vector
Convert the input rdd to RDD of Vector.
cc @mengxr
You can merge this pull request into a Git repository by running:
$ git
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2743#issuecomment-59878121
@pwendell There are two PullRequestBuilder plugins, one is work, another
one (called NewSparkPullRequestBuilder) is still failing.
---
If your project is set up
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2743#issuecomment-60036985
Hold this PR, we may don't need it anymore.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2896
[SPARK-4051] [SQL] [PySQL] Convert Row into dictionary
Added a method to Row to turn row into dict:
```
row = Row(a=1)
row.asDict()
{'a': 1}
```
You can merge this pull
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2895#issuecomment-60292102
@JoshRosen It will be better if we could easily backport them.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2838#discussion_r19304373
--- Diff: python/pyspark/worker.py ---
@@ -131,6 +130,14 @@ def process():
for (aid, accum) in _accumulatorRegistry.items():
pickleSer
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2901#discussion_r19312590
--- Diff: python/pyspark/sql.py ---
@@ -1065,7 +1074,9 @@ def applySchema(self, rdd, schema):
[Row(field1=1, field2=u'row1'),..., Row(field1=3
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2901#discussion_r19313312
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala
---
@@ -372,13 +372,20 @@ private[sql] object JsonRDD extends Logging
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2901#discussion_r19313556
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala
---
@@ -372,13 +372,20 @@ private[sql] object JsonRDD extends Logging
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2901#issuecomment-60321798
Thanks for fix so many typos!
It will be awesome to recognize all Date/Timestamps values in JsonRDD. If
it's not easy to do it in this PR, we could do
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2433#issuecomment-60322408
@holdenk Could you add some examples about how the logging levels should
be? All list all the valid names in docstring.
@tdas We could use this in the Streaming
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2701#discussion_r19314368
--- Diff: python/pyspark/sql.py ---
@@ -305,12 +305,15 @@ class StructField(DataType):
-def __init__(self, name, dataType
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2916
[SPARK-2652] [PySpark] donot use KyroSerializer as default serializer
KyroSerializer can not serialize customized class without registered
explicitly, use it as default serializer in PySpark
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2920
simplify serializer, use AutoBatchedSerializer by default.
This PR simplify serializer, always use batched serializer
(AutoBatchedSerializer as default), even batch size is 1.
You can merge
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2901#discussion_r19346201
--- Diff: python/pyspark/sql.py ---
@@ -1084,10 +1096,11 @@ def applySchema(self, rdd, schema):
... StructField(null, DoubleType(), True
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2901#discussion_r19353769
--- Diff: python/pyspark/sql.py ---
@@ -1084,10 +1096,11 @@ def applySchema(self, rdd, schema):
... StructField(null, DoubleType(), True
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2681#issuecomment-60431415
@JoshRosen Could you look at this again? I had rebased it on your changes.
Hope this could make the tests more stable.
---
If your project is set up for it, you can
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2933
use broadcast for task only when task is large enough
Using broadcast for small tasks has no benefits or even some regressions
(several RPCs), also there some stable issues with broadcast, so we
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2681#issuecomment-60445861
PR #2933 will so similar things as this one, that also works for
HttpBroadcast.
---
If your project is set up for it, you can reply to this email and have your
reply
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2932#issuecomment-60449095
Cool, LGTM!
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2935
[SPARK-4082] remove unnecessary broadcast for conf
We already broadcast the task (RDD and closure) itself, so some small data
used in RDD or closure do not needed to be broadcasted explicitly any
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2681#issuecomment-60452847
Even if we merge #2933, I still would like to have this, because people
could use broadcast for small dataset (such as in MLlib), this patch can
improve these cases
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2933#discussion_r19369470
--- Diff: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
---
@@ -124,6 +123,10 @@ class DAGScheduler(
/** If enabled, we may run
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2935#issuecomment-60468274
But inside readFields(), it may call new Configuration(), so we still need
to synchronize it here.
---
If your project is set up for it, you can reply to this email
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2935#discussion_r19373926
--- Diff: core/src/main/scala/org/apache/spark/SerializableWritable.scala
---
@@ -38,8 +38,10 @@ class SerializableWritable[T : Writable](@transient var
t: T
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2935#issuecomment-60472321
@JoshRosen this PR is ready to review, thanks!
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2716#issuecomment-60473788
failed:
```
[info] - sorting without aggregation, with spill *** FAILED ***
[info] java.io.FileNotFoundException:
/tmp/spark-local-20141024230838-6b0e/07
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2941
[SPARK-4088] [PySpark] Python worker should exit after socket is closed by
JVM
In case of take() or exception in Python, python worker may exit before JVM
read() all the response, then the write
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2941#issuecomment-60474604
The race is that which of reader or writer thread will know that the worker
has exited, If reader find it first, then no problem, but if writer find it
first
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2941#issuecomment-60475340
It's not easy to reproduce this failure, but it did fail in jenkins:
```
==
ERROR
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2941#issuecomment-60475355
Also I can not reproduce this without daemon.py (simulate the behavior in
Windows).
---
If your project is set up for it, you can reply to this email and have your
reply
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2935#issuecomment-60497056
Jenkins, test this please.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2933#discussion_r19377630
--- Diff: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
---
@@ -124,6 +123,10 @@ class DAGScheduler(
/** If enabled, we may run
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2933#discussion_r19377652
--- Diff: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
---
@@ -124,6 +123,10 @@ class DAGScheduler(
/** If enabled, we may run
301 - 400 of 6045 matches
Mail list logo
