Github user davies commented on the issue:
https://github.com/apache/spark/pull/15106
@srowen Could you left an `lgtm` here?
---
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 issue:
https://github.com/apache/spark/pull/15089
@JoshRosen Answer your questions here:
1. This is special designed for Python UDF (we do not have similar
requirement in other place), I'd not to make it general without have a real use
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/15089#discussion_r79253457
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/python/BatchEvalPythonExec.scala
---
@@ -17,18 +17,270 @@
package
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/15089#discussion_r79253378
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/python/BatchEvalPythonExec.scala
---
@@ -17,18 +17,270 @@
package
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15106
@srowen The previous problem is caused by using the default locale of host
to format the numbers, that sounds perfect by caused some problems. So we
fallback to only use English as the locale
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/15089#discussion_r79038500
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/python/BatchEvalPythonExec.scala
---
@@ -17,18 +17,270 @@
package
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/15089#discussion_r79037083
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/python/BatchEvalPythonExec.scala
---
@@ -17,18 +17,270 @@
package
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/15089#discussion_r79034499
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/python/BatchEvalPythonExec.scala
---
@@ -98,7 +353,7 @@ case class BatchEvalPythonExec(udfs
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15106
cc @maver1ck @srowen
---
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
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/15106
[SPARK-16439] [SQL] bring back the separator in SQL UI
## What changes were proposed in this pull request?
Currently, the SQL metrics looks like `number of rows: `, it's
very
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15101
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
enabled and wishes so
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/15103
[SPARK-17100] [SQL] fix Python udf in filter on top of outer join
## What changes were proposed in this pull request?
In optimizer, we try to evaluate the condition to see whether it's
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15026
Merging this into master, 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
enabled
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15076
@hvanhovell Since the optimization rule change the result (or sematics),
I'd like to fix it, not to introduce more complexcity in physical layer. The
saved few cycles may not worth, because people
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15026
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
enabled and wishes so
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15076
@hvanhovell What's the reason that we can not just use the literal use
grouping key?
---
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 commented on the issue:
https://github.com/apache/spark/pull/14537
What's the progress on this one?
---
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
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15068
Merging this into master and 2.0.
---
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
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15068
@JoshRosen Just saw the other patch, 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 commented on the issue:
https://github.com/apache/spark/pull/15068
@JoshRosen The current patch looks good to me, could you also fix the case
that LocalLimit is inserted when we turn a DataFrame with limit into Python RDD?
---
If your project is set up for it, you
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15089
@JoshRosen The current fix looks good to me. Could you also fix the case
that LocalLimit is correctly inserted when we turn a Python DataFrame with
limit into a Python RDD?
---
If your project
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/15082#discussion_r78667613
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
---
@@ -276,6 +276,11 @@ class CodegenContext
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15082
@JoshRosen I think this is a potential bug (not now).
---
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 issue:
https://github.com/apache/spark/pull/15089
cc @JoshRosen @rxin
---
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
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/15089
[SPARK-15621] [SQL] Support spilling for Python UDF
## What changes were proposed in this pull request?
When execute a Python UDF, we buffer the input row into as queue, then pull
them
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/10840#discussion_r78495137
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/metric/SQLMetricsSuite.scala
---
@@ -71,7 +71,9 @@ class SQLMetricsSuite extends
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15030
Merging into 2.0 and master.
---
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
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/15030#discussion_r78435023
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/limit.scala ---
@@ -148,8 +148,8 @@ case class TakeOrderedAndProjectExec
Github user davies commented on the issue:
https://github.com/apache/spark/pull/15026
Once we could log the original stacktrace, this looks good to me.
---
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/15026#discussion_r78432383
--- Diff: python/pyspark/cloudpickle.py ---
@@ -109,6 +109,15 @@ def dump(self, obj):
if 'recursion' in e.args[0]:
msg
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/15026#discussion_r78432125
--- Diff: python/pyspark/broadcast.py ---
@@ -75,7 +75,13 @@ def __init__(self, sc=None, value=None,
pickle_registry=None, path=None):
self
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14919
LGTM, merging into master and 2.0 branch, 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/15030
[SPARK-17474] [SQL] fix python udf in TakeOrderedAndProjectExec
## What changes were proposed in this pull request?
When there is any Python UDF in the Project between Sort and Limit
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14671
@HyukjinKwon That sounds good, 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 issue:
https://github.com/apache/spark/pull/14671
@andreweduffy Good point, but we still use the parquet-mr when there is any
complex type in the schema.
---
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 issue:
https://github.com/apache/spark/pull/14671
Before disable the record level filter in parquet reader, I think pushing
more non-efficient predicates into parquet reader will be even worse, right?
---
If your project is set up for it, you can
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14944
Merging this into 2.0 branch.
---
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
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14927
@hvanhovell Has lgtm offline. Other contributors also confirm that this
patch fix the bug, I'm going to merge this one into master and 2.0 branch.
---
If your project is set up for it, you can
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14690#discussion_r77422471
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/TableFileCatalog.scala
---
@@ -0,0 +1,102 @@
+/*
+ * Licensed
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14517#discussion_r77420949
--- Diff: python/pyspark/sql/readwriter.py ---
@@ -692,8 +734,7 @@ def orc(self, path, mode=None, partitionBy=None,
compression=None
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14517#discussion_r77420246
--- Diff: python/pyspark/sql/readwriter.py ---
@@ -747,16 +800,25 @@ def _test():
except py4j.protocol.Py4JError:
spark = SparkSession
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14866
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
enabled and wishes so
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14797
Merged this into master and 2.0 branch, 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 commented on the issue:
https://github.com/apache/spark/pull/14941
Merging this into master and 2.0 branch, 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 commented on the issue:
https://github.com/apache/spark/pull/14941
@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
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14941
LGTM, pending jenkins.
---
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
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
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14797#discussion_r77394975
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
---
@@ -479,13 +480,23 @@ case class DataSource
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14857
Merging into master and 2.0
---
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
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14857
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
enabled and wishes so
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14176
LGTM, I will merge this one to master (enable us to do more benchmarks with
these two implementations).
---
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 issue:
https://github.com/apache/spark/pull/14515
LGTM, merging this into 2.0 and master, 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/14927
[SPARK-16922] [SPARK-17211] [SQL] make the address of values portable in
LongToUnsafeRowMap
## What changes were proposed in this pull request?
In LongToUnsafeRowMap, we use offset
Github user davies commented on the issue:
https://github.com/apache/spark/pull/11956
We could compress them in memory with MEMORY_AND_DISK_SER, this could be
controlled by a flag.
---
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 the issue:
https://github.com/apache/spark/pull/14607
Merging into master and 2.0 branch.
---
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
Github user davies commented on the issue:
https://github.com/apache/spark/pull/11956
cc @rxin
---
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
Github user davies commented on the issue:
https://github.com/apache/spark/pull/11956
@kiszk The current implementation use ByteBuffer and smart compression
algorithms, it too slow to build the in-memory cache, make it useless. So we'd
like to improve the performance of building
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14176
Can we make this `spark.sql.codegen.aggregate.map.twolevel.enable`
internal? otherwise we should have a better name.
---
If your project is set up for it, you can reply to this email and have your
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14797
cc @yhuai @JoshRosen @rxin
---
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
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/14797
[SPARK-17230] [SQL] Should not pass optimized query into QueryExecution in
DataFrameWriter
## What changes were proposed in this pull request?
Some analyzer rules have assumptions
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14722
@petermaxlee The `Batch` means insert multiple rows into JDBC data source
using single query, the context is JDBC data source, not streaming. The
SPARK-13286 has more context on that.
---
If your
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14722
@petermaxlee Before this PR, the underlying cause is NOT included in the
logging, the description had been corrected.
---
If your project is set up for it, you can reply to this email and have
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14607#discussion_r75949718
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/command/ddl.scala ---
@@ -518,21 +550,87 @@ case class AlterTableRecoverPartitionsCommand
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14607#discussion_r75947797
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/command/ddl.scala ---
@@ -518,21 +550,87 @@ case class AlterTableRecoverPartitionsCommand
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14607#discussion_r75947173
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/command/ddl.scala ---
@@ -443,6 +446,31 @@ case class AlterTableDropPartitionCommand
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14722
Merging this into master and 2.0 branch.
---
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 a diff in the pull request:
https://github.com/apache/spark/pull/14692#discussion_r75615959
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
---
@@ -584,15 +584,18 @@ class CodegenContext
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14692
@cloud-fan Could you review this one?
---
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 a diff in the pull request:
https://github.com/apache/spark/pull/14567#discussion_r75553470
--- Diff: dev/py-validate.sh ---
@@ -0,0 +1,110 @@
+#!/usr/bin/env bash
--- End diff --
Where is this file used?
---
If your project is set
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14567#discussion_r75553298
--- Diff: python/pyspark/cloudpickle.py ---
@@ -42,17 +42,17 @@
"""
--- End diff --
This file is copied, please ignore i
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14567#discussion_r75553255
--- Diff: python/pyspark/heapq3.py ---
@@ -408,10 +408,12 @@
__all__ = ['heappush', 'heappop', 'heapify', 'heapreplace', 'merge
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14567#discussion_r75553180
--- Diff: python/pyspark/ml/param/shared.py ---
@@ -25,7 +25,8 @@ class HasMaxIter(Params):
Mixin for param maxIter: max number of iterations (>
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/14722
[SPARK-13286] [SQL] add the next expression of SQLException as cause
## What changes were proposed in this pull request?
Some JDBC driver (for example PostgreSQL) does not use
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14693
Merging this into master and 2.0 and 1.6 (hopefully), 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
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14693#discussion_r75529799
--- Diff:
core/src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeExternalSorter.java
---
@@ -522,7 +522,7 @@ public long spill() throws
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14693
I'm sorry that did not pay enough attension on this part, thanks to the
unit test!
---
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 commented on the issue:
https://github.com/apache/spark/pull/14693
@sitalkedia Your last commit is not correct, which fail this test.
`upstream` is the one used for reading, `inMemIterator` is the one used for
spilling, see #10142
---
If your project is set up
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14452
@viirya Had a quick look on this one, It seems that we are trying to make
the logical plans looks better, but does not help much for actual physical plan
or runtime. For example, for self join
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14693
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
enabled and wishes so
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/14692
decrease the threshold when split expressions
## What changes were proposed in this pull request?
In 2.0, we change the threshold of splitting expressions from 16K to 64K,
which cause very
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14685
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
enabled and wishes so
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14685#discussion_r75128301
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/subquery.scala ---
@@ -56,30 +44,29 @@ trait ExecSubqueryExpression extends
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14631
LGTM, merging this into master.
---
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
Github user davies commented on the issue:
https://github.com/apache/spark/pull/11956
@kiszk I'm sorry that I do not have the bandwidth to review this,
https://github.com/apache/spark/pull/13899/files sounds like an easier approach
(have not looked into the details), how do you think
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/13680#discussion_r74798477
--- Diff:
sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeArrayData.java
---
@@ -25,55 +25,57 @@
import
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14631
The description is not correct, we keep the microsecond but lost precision
in some corner cases, could you update that (also title)?
---
If your project is set up for it, you can reply
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14631#discussion_r74703839
--- Diff: python/pyspark/sql/tests.py ---
@@ -183,6 +183,13 @@ def test_empty_row(self):
self.assertEqual(len(row), 0)
+class
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14607
@yhuai @sameeragarwal @rxin I had updated the MSCK REPAIR TABLE to list all
the leaf files in parallel to avoid the listing in Hive metastore, hopefully
this could speed up it a lot (not benchmarked
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14469
@JoshRosen ping
---
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
GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/14607
[SPARK-16905] SQL DDL: MSCK REPAIR TABLE (follow-up)
## What changes were proposed in this pull request?
This PR split the the single `createPartitions()` call into smaller
batches, which
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14500#discussion_r74481008
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/command/ddl.scala ---
@@ -425,6 +430,111 @@ case class AlterTableDropPartitionCommand
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14548
Merging it into master, 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
enabled
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14548
@hvanhovell Had posted an picture, check it out.
---
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/14548#discussion_r74340389
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/subquery.scala ---
@@ -17,42 +17,77 @@
package org.apache.spark.sql.execution
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14548#discussion_r74340710
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/subquery.scala ---
@@ -68,14 +103,90 @@ case class ScalarSubquery
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14548#discussion_r74340195
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
---
@@ -502,15 +508,64 @@ case class OutputFakerExec(output
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14548#discussion_r74338195
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/subquery.scala ---
@@ -68,14 +103,90 @@ case class ScalarSubquery
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14469#discussion_r74337946
--- Diff: python/pyspark/sql/session.py ---
@@ -432,14 +430,9 @@ def createDataFrame(self, data, schema=None,
samplingRatio=None):
``byte
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/14469#discussion_r74337920
--- Diff: python/pyspark/sql/tests.py ---
@@ -411,6 +411,21 @@ def test_infer_schema_to_local(self):
df3 = self.spark.createDataFrame(rdd
Github user davies commented on the issue:
https://github.com/apache/spark/pull/14513
LGTM, merging into master, 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
enabled
201 - 300 of 6045 matches
Mail list logo
