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--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/catalog/SessionCatalogSuite.scala
---
@@ -465,6 +466,48 @@ class SessionCatalogSuite
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--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala ---
@@ -125,11 +132,16 @@ private[hive] class
HiveMetastoreCatalog
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--- Diff:
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---
@@ -767,7 +857,45 @@ class Analyzer(
}
}
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--- Diff:
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@@ -845,6 +846,7 @@ private[hive] class HiveClientImpl(
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--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLViewBackwardCompatibilitySuite.scala
---
@@ -0,0 +1,113 @@
+/*
+ * Licen
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--- Diff:
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@@ -0,0 +1,113 @@
+/*
+ * Licen
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+/*
+ * Licen
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@@ -767,7 +857,45 @@ class Analyzer(
}
}
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@@ -767,7 +857,45 @@ class Analyzer(
}
}
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@@ -510,32 +539,93 @@ class Analyzer(
* Replaces
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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
---
@@ -2476,4 +2476,17 @@ class SQLQuerySuite extends QueryTest with
SharedSQ
Github user jkbradley commented on the issue:
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Yikes, thanks for fixing this!
LGTM
Merging with master
I'll also try to merge it with branch-2.1, branch-2.0, branch-1.6 but will
say if I run into issues.
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Github user srowen commented on the issue:
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How does this relate to https://github.com/apache/spark/pull/15848 ?
As I understand you already hit problems and were not able to debug them.
What's different here?
I was going to close the
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@hvanhovell
Can you please review the changes
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SPARK-9487][Tests] Begin the work of robustifying unit tests , start with
ContextCleanerSuite
â¦tests
## What changes were proposed in this pull request?
This is a work in progress p
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[SPARK-19118] [SQL] Percentile support for frequency distribution table
## What changes were proposed in this pull request?
I have a frequency distribution table with following entries
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Github user kayousterhout commented on the issue:
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It looks like you've added multi-threading for task serialization here,
which I'm hesitant about for reasons @squito discussed in the JIRA (namely, I
think reducing the size of the data serial
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LGTM
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Github user dongjoon-hyun commented on the issue:
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Thank you, @gatorsmile . I updated the commit and description of this PR.
You can see the new image from generated doc.
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--- Diff: docs/sql-programming-guide.md ---
@@ -1362,6 +1362,13 @@ options.
- Dataset and DataFrame API `explode` has been deprecated, alternative
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--- Diff: docs/sql-programming-guide.md ---
@@ -1362,6 +1362,13 @@ options.
- Dataset and DataFrame API `explode` has been deprecated, alternative
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retest this please
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--- Diff:
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@@ -385,6 +380,8 @@ final class DataFrameWriter[T] private[sql](ds:
Datas
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thanks for the review, merging to master!
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Thank you for approving, @srowen .
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@@ -340,3 +341,91 @@ object CaseKeyWhen {
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cc @cloud-fan
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[SPARK-16101][SQL] Refactoring CSV write path to be consistent with JSON
data source
## What changes were proposed in this pull request?
This PR refactors CSV write path to be consiste
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--- Diff: R/pkg/R/mllib_utils.R ---
@@ -80,9 +81,9 @@ predict_internal <- function(object, newData) {
#' model <- read.ml(path)
#' }
#' @not
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Ah, thank you.
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Github user srowen commented on the issue:
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Yeah, that's great. That narrows down the fix a bit.
I bet there are other places in tests where we could use the same logic, to
only ignore the error on Windows, but unless you know of obvious pl
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--- Diff: docs/streaming-programming-guide.md ---
@@ -630,35 +630,106 @@ which creates a DStream from text
data received over a TCP socket connection. Bes
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--- Diff:
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@@ -235,18 +236,97 @@ class InputStreamsSuite extends TestSuiteBase
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--- Diff: docs/streaming-programming-guide.md ---
@@ -630,35 +630,106 @@ which creates a DStream from text
data received over a TCP socket connection. Bes
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--- Diff:
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Github user HyukjinKwon commented on the issue:
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I made a new function just simply because it repeats the same logics.
Either way is fine with me.
So.. do you mean something like the one as below?
```scala
try {
Util
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Github user srowen commented on the issue:
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@hustfxj please fix the description
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Github user hustfxj commented on the issue:
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@vanzin @srowen @dongjoon-hyun can you review again ? and help me review
[SPARK-18959] and [SPARK-19052], thank you very much.
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