[GitHub] spark issue #13891: [SPARK-6685][MLLIB]Use DSYRK to compute AtA in ALS
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[GitHub] spark issue #13891: [SPARK-6685][MLLIB]Use DSYRK to compute AtA in ALS
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[GitHub] spark issue #13891: [SPARK-6685][MLLIB]Use DSYRK to compute AtA in ALS
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[GitHub] spark issue #13891: [SPARK-6685][MLLIB]Use DSYRK to compute AtA in ALS
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[GitHub] spark pull request #15513: [SPARK-17963][SQL][Documentation] Add examples (e...
Github user HyukjinKwon commented on a diff in the pull request: https://github.com/apache/spark/pull/15513#discussion_r84615167 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Covariance.scala --- @@ -76,8 +76,14 @@ abstract class Covariance(x: Expression, y: Expression) extends DeclarativeAggre } } + --- End diff -- This wouldn't be a nit because most of case class definitions across expressions seem have double-spaced indentation. Also, it seems fine - https://github.com/databricks/scala-style-guide#blank-lines-vertical-whitespace > Use one or two blank line(s) to separate class definitions. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #13891: [SPARK-6685][MLLIB]Use DSYRK to compute AtA in ALS
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[GitHub] spark issue #13891: [SPARK-6685][MLLIB]Use DSYRK to compute AtA in ALS
Github user SparkQA commented on the issue: https://github.com/apache/spark/pull/13891 **[Test build #67422 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/67422/consoleFull)** for PR 13891 at commit [`d29fd67`](https://github.com/apache/spark/commit/d29fd67a2a24675b7be2f7f51ba170fda11a85d7). * This patch **fails Scala style tests**. * This patch merges cleanly. * This patch adds no public classes. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #13891: [SPARK-6685][MLLIB]Use DSYRK to compute AtA in ALS
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[GitHub] spark issue #13891: [SPARK-6685][MLLIB]Use DSYRK to compute AtA in ALS
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[GitHub] spark issue #15513: [SPARK-17963][SQL][Documentation] Add examples (extend) ...
Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/15513 I have another question. I found this PR also use `expressions` in the description when the function only accepts foldable expressions. This is also unclear to the users. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15513: [SPARK-17963][SQL][Documentation] Add examples (e...
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/15513#discussion_r84613013
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/CallMethodViaReflection.scala
---
@@ -43,11 +43,20 @@ import org.apache.spark.util.Utils
* and the second element should be a literal string for
the method name,
* and the remaining are input arguments to the Java
method.
*/
-// scalastyle:off line.size.limit
@ExpressionDescription(
- usage = "_FUNC_(class,method[,arg1[,arg2..]]) calls method with
reflection",
- extended = "> SELECT _FUNC_('java.util.UUID', 'randomUUID');\n
c33fb387-8500-4bfa-81d2-6e0e3e930df2")
-// scalastyle:on line.size.limit
+ usage = "_FUNC_(class, method[, arg1[, arg2 ..]]) - Calls method with
reflection.",
+ extended = """
+Arguments:
+ class - a string literal that represents a fully-qualified class
name.
+ method - a string literal that represents a method name.
+ arg - a boolean, numeric or string expression that represents
arguments for the method.
--- End diff --
Do we support decimal?
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[GitHub] spark issue #15513: [SPARK-17963][SQL][Documentation] Add examples (extend) ...
Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/15513 To differentiate literals from expressions, the simplest way is to add `expr` or `expression` into the function name. For the arguments whose names do not contain `expr`, they are treated as literal. I know there are multiple exceptions. For example, the input might be neither expressions nor literals. Then, we can explain it in the description. Below is the online doc of Oracle functions: https://docs.oracle.com/cd/E11882_01/server.112/e41084/functions115.htm#SQLRF00680 --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15579: Added support for extra command in front of spark.
Github user sheepduke commented on the issue: https://github.com/apache/spark/pull/15579 @srowen Hi, at first we wanted to add support for numactl only, but later we thought that it is rather better to make it possible for adding the prefix command. It is not only for NUMA, but also for other optimization tools. This feature makes life a lot easier when spark is called from a script or so. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #13252: [SPARK-15473][SQL] CSV data source writes header for emp...
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[GitHub] spark issue #13252: [SPARK-15473][SQL] CSV data source writes header for emp...
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[GitHub] spark issue #13252: [SPARK-15473][SQL] CSV data source writes header for emp...
Github user SparkQA commented on the issue: https://github.com/apache/spark/pull/13252 **[Test build #67421 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/67421/consoleFull)** for PR 13252 at commit [`031c9da`](https://github.com/apache/spark/commit/031c9dacba77c6197626d02ceb0e1081b18e187b). * This patch passes all tests. * This patch merges cleanly. * This patch adds no public classes. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15603: [WEBUI][MINOR] Return types in methods + cleanup
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[GitHub] spark issue #15603: [WEBUI][MINOR] Return types in methods + cleanup
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[GitHub] spark issue #15603: [WEBUI][MINOR] Return types in methods + cleanup
Github user SparkQA commented on the issue: https://github.com/apache/spark/pull/15603 **[Test build #67420 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/67420/consoleFull)** for PR 15603 at commit [`6fcd247`](https://github.com/apache/spark/commit/6fcd247f546c2cfe15f6909bf8a9d75dc822ef15). * This patch passes all tests. * This patch merges cleanly. * This patch adds no public classes. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15513: [SPARK-17963][SQL][Documentation] Add examples (extend) ...
Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15513 IMHO, I would like to leave it and prefer to differentiate literal from expression as it throws an exception, for example, when a column is given as an argument for literal, the exception message usually says something like "the argument should be a string literal". --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15604: [SPARK-18066] [CORE] [TESTS] Add Pool usage policies tes...
Github user AmplabJenkins commented on the issue: https://github.com/apache/spark/pull/15604 Can one of the admins verify this patch? --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15604: [SPARK-18066] [CORE] [TESTS] Add Pool usage policies tes...
Github user erenavsarogullari commented on the issue: https://github.com/apache/spark/pull/15604 cc @kayousterhout @markhamstra --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15604: Add Pool usage policies test coverage for FIFO & ...
GitHub user erenavsarogullari opened a pull request: https://github.com/apache/spark/pull/15604 Add Pool usage policies test coverage for FIFO & FAIR Schedulers ## What changes were proposed in this pull request? The following FIFO & FAIR Schedulers Pool usage cases need to have unit test coverage : - FIFO Scheduler just uses **root pool** so even if `spark.scheduler.pool` property is set, related pool is not created and `TaskSetManagers` are added to **root pool**. - FAIR Scheduler uses `default pool` when `spark.scheduler.pool` property is not set. This can be happened when - `Properties` object is **null** - `Properties` object is **empty**(`new Properties()`) - It points **default pool**(`spark.scheduler.pool=default`). - FAIR Scheduler creates a **new pool** with **default values** when `spark.scheduler.pool` property points **non-existent** pool. This can be happened when **scheduler allocation file** is not set or it does not contain related pool. ## How was this patch tested? New Unit tests are added. You can merge this pull request into a Git repository by running: $ git pull https://github.com/erenavsarogullari/spark SPARK-18066 Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/15604.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #15604 commit 9e588cf33ea3a99b384399a7b444ee7fb9df82d5 Author: erenavsarogullari Date: 2016-10-23T20:37:26Z Add Pool usage policies test coverage for FIFO & FAIR Schedulers --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15513: [SPARK-17963][SQL][Documentation] Add examples (extend) ...
Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15513 Thanks @gatorsmile. I will double-check if there is any instance more that misses default value. For the format, I asked @rxin initially to avoid change a lot repeatedly. Could I please ask what do you think of the suggested format? I would like to confirm it before proceeding to sweep it - @srowen @rxin @jodersky. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15441: [SPARK-4411] [Web UI] Add "kill" link for jobs in the UI
Github user ajbozarth commented on the issue: https://github.com/apache/spark/pull/15441 @srowen Addressed the try-finally, this look good to go 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 this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15513: [SPARK-17963][SQL][Documentation] Add examples (e...
Github user HyukjinKwon commented on a diff in the pull request: https://github.com/apache/spark/pull/15513#discussion_r84604637 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala --- @@ -49,21 +49,29 @@ import org.apache.spark.sql.types._ * DEFAULT_PERCENTILE_ACCURACY. */ @ExpressionDescription( - usage = -""" - _FUNC_(col, percentage [, accuracy]) - Returns the approximate percentile value of numeric + usage = """ +_FUNC_(col, percentage [, accuracy]) - Returns the approximate percentile value of numeric column `col` at the given percentage. The value of percentage must be between 0.0 and 1.0. The `accuracy` parameter (default: 1) is a positive integer literal which controls approximation accuracy at the cost of memory. Higher value of `accuracy` yields better accuracy, `1.0/accuracy` is the relative error of the approximation. - - _FUNC_(col, array(percentage1 [, percentage2]...) [, accuracy]) - Returns the approximate - percentile array of column `col` at the given percentage array. Each value of the - percentage array must be between 0.0 and 1.0. The `accuracy` parameter (default: 1) is - a positive integer literal which controls approximation accuracy at the cost of memory. - Higher value of `accuracy` yields better accuracy, `1.0/accuracy` is the relative error of - the approximation. -""") + When percentage is an array, each value of the percentage array must be between 0.0 and 1.0. + In this case, returns the approximate percentile array of column `col` at the given + percentage array. + """, + extended = """ +Arguments: + col - a numeric expression. + percentage - a numeric literal or an array literal of numeric type that defines the +percentile between 0.0 and 1.0. For example, 0.5 means 50-percentile. + accuracy - a numeric literal that defines approximation accuracy. --- End diff -- expression takes both value and column where as literal takes value only in general. (It throws an exception when a column is given instead). --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15513: [SPARK-17963][SQL][Documentation] Add examples (e...
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/15513#discussion_r84604598
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/xml/xpath.scala
---
@@ -150,8 +206,16 @@ case class XPathString(xml: Expression, path:
Expression) extends XPathExtract {
// scalastyle:off line.size.limit
@ExpressionDescription(
- usage = "_FUNC_(xml, xpath) - Returns a string array of values within
xml nodes that match the xpath expression",
- extended = "> SELECT
_FUNC_('b1b2b3c1c2','a/b/text()');\n['b1','b2','b3']")
+ usage = "_FUNC_(xml, xpath) - Returns a string array of values within
the nodes of xml that match the XPath expression.",
+ extended = """
+Arguments:
+ xml - a string expression that represents XML document.
+ path - a string literal that represents XPath expression.
--- End diff --
expression takes both value and column where as literal takes value only in
general.
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[GitHub] spark issue #15553: [SPARK-18008] [build] Add support for -Dmaven.test.skip=...
Github user mridulm commented on the issue: https://github.com/apache/spark/pull/15553 @srowen This is explicitly supports maven.test.skip=true - the rationale for using it can be project specific (generating clean builds for various profile combinations, internal release builds from an apache tagged released version, etc for example). We are seeing close to halving the build time for clean builds (use of zinc, batched build, etc is already enabled). Regarding complexity of the build - if there are any suggestions on how to reduce that, please do let me know. The pr primarily reorganizes all test scope dependencies into a profile of its own which is activated by default unless maven.test.skip=true; which seems to be the only recommended way to do it from maven docs/discussions. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #13252: [SPARK-15473][SQL] CSV data source writes header for emp...
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[GitHub] spark pull request #15602: [SPARK-18058][SQL] [BRANCH-2.0]Comparing column t...
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[GitHub] spark issue #15602: [SPARK-18058][SQL] [BRANCH-2.0]Comparing column types ig...
Github user hvanhovell commented on the issue: https://github.com/apache/spark/pull/15602 Merging to branch-2.0. Thanks! Can you close 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 does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15541: [SPARK-17637][Scheduler]Packed scheduling for Spark task...
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[GitHub] spark issue #15541: [SPARK-17637][Scheduler]Packed scheduling for Spark task...
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[GitHub] spark issue #15541: [SPARK-17637][Scheduler]Packed scheduling for Spark task...
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[GitHub] spark issue #15441: [SPARK-4411] [Web UI] Add "kill" link for jobs in the UI
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[GitHub] spark issue #15441: [SPARK-4411] [Web UI] Add "kill" link for jobs in the UI
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[GitHub] spark issue #15441: [SPARK-4411] [Web UI] Add "kill" link for jobs in the UI
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[GitHub] spark issue #15602: [SPARK-18058][SQL] [BRANCH-2.0]Comparing column types ig...
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[GitHub] spark issue #15602: [SPARK-18058][SQL] [BRANCH-2.0]Comparing column types ig...
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[GitHub] spark issue #15602: [SPARK-18058][SQL] [BRANCH-2.0]Comparing column types ig...
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[GitHub] spark issue #15603: [WEBUI][MINOR] Return types in methods + cleanup
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[GitHub] spark pull request #15603: [WEBUI][MINOR] Return types in methods + cleanup
GitHub user jaceklaskowski opened a pull request: https://github.com/apache/spark/pull/15603 [WEBUI][MINOR] Return types in methods + cleanup ## What changes were proposed in this pull request? The main purpose of the change is to discuss the purpose of `SparkUITab` class and `appUIAddress` attribute since they seem to introduce nothing new. Once agreed they're not needed I'm going to remove the comment. Code cleanup ## How was this patch tested? Local build You can merge this pull request into a Git repository by running: $ git pull https://github.com/jaceklaskowski/spark sparkui-fixes Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/15603.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #15603 commit 6fcd247f546c2cfe15f6909bf8a9d75dc822ef15 Author: Jacek Laskowski Date: 2016-10-23T19:45:21Z [WEBUI][MINOR] Return types in methods + cleanup --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #11119: [SPARK-10780][ML] Add an initial model to kmeans
Github user yinxusen commented on the issue: https://github.com/apache/spark/pull/9 How about the following: 1. Since the new generated model is derived from an estimator, the model should have the same params as its parent estimator. That's why there is no need to consider about params of model. We can only care about params of the estimator, as we have already done in the code - the param k and param initMode. 2. We can treat initialModel as a "transient" variable so that it must be vanished facing serialization, since there is no need to hold initialModel in a new generated model. 3. We can introduce a dumb model as a placeholder for initialModel, as a consequence, users know the initialization method of the model. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15602: [SPARK-18058][SQL] [BRANCH-2.0]Comparing column types ig...
Github user hvanhovell commented on the issue: https://github.com/apache/spark/pull/15602 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 so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15596: [SQL] Remove shuffle codes in CollectLimitExec
Github user hvanhovell commented on the issue: https://github.com/apache/spark/pull/15596 @JoshRosen could you shed some light on why we are not using the regular `EnsureRequirements` based code path for `CollectLimitExec`? --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15595: [SPARK-18058][SQL] Comparing column types ignorin...
Github user CodingCat commented on a diff in the pull request:
https://github.com/apache/spark/pull/15595#discussion_r84600741
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
---
@@ -377,4 +377,23 @@ class AnalysisSuite extends AnalysisTest {
assertExpressionType(sum(Divide(Decimal(1), 2.0)), DoubleType)
assertExpressionType(sum(Divide(1.0, Decimal(2.0))), DoubleType)
}
+
+ test("SPARK-18058: union and set operations shall not care about the
nullability" +
+" when comparing column types") {
+val firstTable = LocalRelation(
+ AttributeReference("a",
+StructType(Seq(StructField("a", IntegerType, nullable = true))),
nullable = false)())
+val secondTable = LocalRelation(
+ AttributeReference("a",
+StructType(Seq(StructField("a", IntegerType, nullable = false))),
nullable = false)())
+
+val unionPlan = Union(firstTable, secondTable)
+assertAnalysisSuccess(unionPlan)
+
+val r1 = Except(firstTable, secondTable)
--- End diff --
nice catch, I have followed this in the backport version of the patch
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[GitHub] spark issue #15602: [SPARK-18058][SQL] [BRANCH-2.0]Comparing column types ig...
Github user SparkQA commented on the issue: https://github.com/apache/spark/pull/15602 **[Test build #67419 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/67419/consoleFull)** for PR 15602 at commit [`e0d806a`](https://github.com/apache/spark/commit/e0d806a5dc7698079f188851044b3cc1e0e39bb3). --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15602: [SPARK-18058][SQL] [BACKPORT-2.0]Comparing column...
GitHub user CodingCat opened a pull request: https://github.com/apache/spark/pull/15602 [SPARK-18058][SQL] [BACKPORT-2.0]Comparing column types ignoring Nullability in Union and SetOperation ## What changes were proposed in this pull request? The PR tries to fix [SPARK-18058](https://issues.apache.org/jira/browse/SPARK-18058) which refers to a bug that the column types are compared with the extra care about Nullability in Union and SetOperation. This PR converts the columns types by setting all fields as nullable before comparison ## How was this patch tested? regular unit test cases You can merge this pull request into a Git repository by running: $ git pull https://github.com/CodingCat/spark branch-2.0 Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/15602.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #15602 commit ce4b93c1d7046b7a3e4bee4e924fd012f315f2ef Author: CodingCat Date: 2016-10-23T17:57:31Z SPARK-18058 commit e0d806a5dc7698079f188851044b3cc1e0e39bb3 Author: CodingCat Date: 2016-10-23T17:59:57Z SPARK-18058 --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15589: [SPARKR][branch-2.0] R merge API doc and example ...
Github user felixcheung closed the pull request at: https://github.com/apache/spark/pull/15589 --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15589: [SPARKR][branch-2.0] R merge API doc and example fix
Github user felixcheung commented on the issue: https://github.com/apache/spark/pull/15589 merged to branch-2.0 and then cherry-picked to master for the error message fix not in 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 and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15541: [SPARK-17637][Scheduler]Packed scheduling for Spark task...
Github user SparkQA commented on the issue: https://github.com/apache/spark/pull/15541 **[Test build #67418 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/67418/consoleFull)** for PR 15541 at commit [`6b29002`](https://github.com/apache/spark/commit/6b29002c29fecdbe32159dd0d31f53716630de46). --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15595: [SPARK-18058][SQL] Comparing column types ignoring Nulla...
Github user tejasapatil commented on the issue: https://github.com/apache/spark/pull/15595 Just saw that this got merged. I had a tiny nit but its ok without it. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15595: [SPARK-18058][SQL] Comparing column types ignorin...
Github user tejasapatil commented on a diff in the pull request:
https://github.com/apache/spark/pull/15595#discussion_r84600424
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
---
@@ -377,4 +377,23 @@ class AnalysisSuite extends AnalysisTest {
assertExpressionType(sum(Divide(Decimal(1), 2.0)), DoubleType)
assertExpressionType(sum(Divide(1.0, Decimal(2.0))), DoubleType)
}
+
+ test("SPARK-18058: union and set operations shall not care about the
nullability" +
+" when comparing column types") {
+val firstTable = LocalRelation(
+ AttributeReference("a",
+StructType(Seq(StructField("a", IntegerType, nullable = true))),
nullable = false)())
+val secondTable = LocalRelation(
+ AttributeReference("a",
+StructType(Seq(StructField("a", IntegerType, nullable = false))),
nullable = false)())
+
+val unionPlan = Union(firstTable, secondTable)
+assertAnalysisSuccess(unionPlan)
+
+val r1 = Except(firstTable, secondTable)
--- End diff --
nit: this var could have been named better.
Actually, you could have gotten rid of the vars by doing :
```
assertAnalysisSuccess(Union(firstTable, secondTable))
assertAnalysisSuccess(Except(firstTable, secondTable))
assertAnalysisSuccess(Intersect(firstTable, secondTable))
```
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[GitHub] spark issue #15441: [SPARK-4411] [Web UI] Add "kill" link for jobs in the UI
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[GitHub] spark issue #15595: [SPARK-18058][SQL] Comparing column types ignoring Nulla...
Github user hvanhovell commented on the issue: https://github.com/apache/spark/pull/15595 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 and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15595: [SPARK-18058][SQL] Comparing column types ignoring Nulla...
Github user CodingCat commented on the issue: https://github.com/apache/spark/pull/15595 sure, doing that 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 this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15595: [SPARK-18058][SQL] Comparing column types ignoring Nulla...
Github user hvanhovell commented on the issue: https://github.com/apache/spark/pull/15595 @CodingCat could you open a backport for branch-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 and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15595: [SPARK-18058][SQL] Comparing column types ignorin...
Github user asfgit closed the pull request at: https://github.com/apache/spark/pull/15595 --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15595: [SPARK-18058][SQL] Comparing column types ignoring Nulla...
Github user hvanhovell commented on the issue: https://github.com/apache/spark/pull/15595 LGTM - merging to 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 and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #14136: [SPARK-16282][SQL] Implement percentile SQL function.
Github user hvanhovell commented on the issue: https://github.com/apache/spark/pull/14136 It is relatively straight forward to test `ImperativeAggregate`s. See: - org.apache.spark.sql.catalyst.expressions.aggregate.HyperLogLogPlusPlusSuite - org.apache.spark.sql.catalyst.expressions.aggregate.ApproximatePercentileSuite For some inspiration. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15441: [SPARK-4411] [Web UI] Add "kill" link for jobs in...
Github user ajbozarth commented on a diff in the pull request:
https://github.com/apache/spark/pull/15441#discussion_r84599733
--- Diff: core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala ---
@@ -651,6 +671,15 @@ class UISeleniumSuite extends SparkFunSuite with
WebBrowser with Matchers with B
}
}
+ def getResponseCode(url: URL, method: String): Int = {
+val connection = url.openConnection().asInstanceOf[HttpURLConnection]
+connection.setRequestMethod(method)
+connection.connect()
+val code = connection.getResponseCode()
+connection.disconnect()
--- End diff --
Thanks, I didn't know scala could do that (how it returns), still learning
new things every day
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[GitHub] spark issue #15417: [SPARK-17851][SQL][TESTS] Make sure all test sqls in cat...
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[GitHub] spark issue #15513: [SPARK-17963][SQL][Documentation] Add examples (extend) ...
Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/15513 We should also add the default value in the argument description. Below is an example. ``` Arguments: col - a numeric expression. percentage - a numeric literal or an array literal of numeric type that defines the percentile between 0.0 and 1.0. For example, 0.5 means 50-percentile. accuracy - a numeric literal that defines approximation accuracy. ``` -> ``` Arguments: col - Data type: numeric. percentage - the percentile between 0.0 and 1.0. For example, 0.5 means 50-percentile. Data type: numeric or an array expression of numeric type. accuracy - approximation accuracy. Data type: numeric. Default: 1. ``` --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15513: [SPARK-17963][SQL][Documentation] Add examples (extend) ...
Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/15513 Another example: ``` Arguments: expr1 - a numeric expression. expr2 - a numeric expression. ``` -> ``` Arguments: expr1 - Data type: numeric. expr2 - Data type: numeric. ``` --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15513: [SPARK-17963][SQL][Documentation] Add examples (extend) ...
Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/15513 I prefer to minimizing the words without showing any information. Below is an example. ``` Arguments: class - a string literal that represents a fully-qualified class name. method - a string literal that represents a method name. arg - a boolean, numeric or string expression that represents arguments for the method. ``` -> ``` Arguments: class - a fully-qualified class name. Data type: string. method - a method name. Data type: string. arg - arguments for the method. Data type: boolean, numeric or string ``` --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15513: [SPARK-17963][SQL][Documentation] Add examples (e...
Github user gatorsmile commented on a diff in the pull request: https://github.com/apache/spark/pull/15513#discussion_r84597837 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala --- @@ -49,21 +49,29 @@ import org.apache.spark.sql.types._ * DEFAULT_PERCENTILE_ACCURACY. */ @ExpressionDescription( - usage = -""" - _FUNC_(col, percentage [, accuracy]) - Returns the approximate percentile value of numeric + usage = """ +_FUNC_(col, percentage [, accuracy]) - Returns the approximate percentile value of numeric column `col` at the given percentage. The value of percentage must be between 0.0 and 1.0. The `accuracy` parameter (default: 1) is a positive integer literal which controls approximation accuracy at the cost of memory. Higher value of `accuracy` yields better accuracy, `1.0/accuracy` is the relative error of the approximation. - - _FUNC_(col, array(percentage1 [, percentage2]...) [, accuracy]) - Returns the approximate - percentile array of column `col` at the given percentage array. Each value of the - percentage array must be between 0.0 and 1.0. The `accuracy` parameter (default: 1) is - a positive integer literal which controls approximation accuracy at the cost of memory. - Higher value of `accuracy` yields better accuracy, `1.0/accuracy` is the relative error of - the approximation. -""") + When percentage is an array, each value of the percentage array must be between 0.0 and 1.0. + In this case, returns the approximate percentile array of column `col` at the given + percentage array. + """, + extended = """ +Arguments: + col - a numeric expression. + percentage - a numeric literal or an array literal of numeric type that defines the +percentile between 0.0 and 1.0. For example, 0.5 means 50-percentile. + accuracy - a numeric literal that defines approximation accuracy. --- End diff -- What is the difference between `a numeric expression` and `a numeric literal`? --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15513: [SPARK-17963][SQL][Documentation] Add examples (e...
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/15513#discussion_r84597661
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala
---
@@ -692,9 +722,11 @@ case class DenseRank(children: Seq[Expression])
extends RankLike {
* change in rank. This is an internal parameter and will
be assigned by the
* Analyser.
*/
-@ExpressionDescription(usage =
- """_FUNC_() - PERCENT_RANK() The PercentRank function computes the
percentage
- ranking of a value in a group of values.""")
+@ExpressionDescription(
+ usage = """
+_FUNC_() - PERCENT_RANK() The PercentRank function computes the
percentage
--- End diff --
`The PercentRank function computes the percentage` -> `Computes the
percentage`
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[GitHub] spark pull request #15513: [SPARK-17963][SQL][Documentation] Add examples (e...
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/15513#discussion_r84597610
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/xml/xpath.scala
---
@@ -150,8 +206,16 @@ case class XPathString(xml: Expression, path:
Expression) extends XPathExtract {
// scalastyle:off line.size.limit
@ExpressionDescription(
- usage = "_FUNC_(xml, xpath) - Returns a string array of values within
xml nodes that match the xpath expression",
- extended = "> SELECT
_FUNC_('b1b2b3c1c2','a/b/text()');\n['b1','b2','b3']")
+ usage = "_FUNC_(xml, xpath) - Returns a string array of values within
the nodes of xml that match the XPath expression.",
+ extended = """
+Arguments:
+ xml - a string expression that represents XML document.
+ path - a string literal that represents XPath expression.
--- End diff --
What is the differences between `a string expression` and `a string
literal`?
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[GitHub] spark pull request #15513: [SPARK-17963][SQL][Documentation] Add examples (e...
Github user gatorsmile commented on a diff in the pull request: https://github.com/apache/spark/pull/15513#discussion_r84597530 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathExpressions.scala --- @@ -970,9 +1270,19 @@ case class Round(child: Expression, scale: Expression) * also known as Gaussian rounding or bankers' rounding. * round(2.5) = 2.0, round(3.5) = 4.0. */ +// scalastyle:off line.size.limit @ExpressionDescription( - usage = "_FUNC_(x, d) - Round x to d decimal places using HALF_EVEN rounding mode.", - extended = "> SELECT _FUNC_(2.5, 0);\n 2.0") + usage = "_FUNC_(expr, d) - Round expr to d decimal places using HALF_EVEN rounding mode.", --- End diff -- Add `Returns` at the beginning. --- 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 is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] spark pull request #15433: [SPARK-17822][SPARKR] Use weak reference in JVMOb...
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Github user hvanhovell commented on the issue: https://github.com/apache/spark/pull/15601 LGTM. Merging to branch-2.0. Could you close 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 project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] spark issue #15513: [SPARK-17963][SQL][Documentation] Add examples (extend) ...
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[GitHub] spark issue #15513: [SPARK-17963][SQL][Documentation] Add examples (extend) ...
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[GitHub] spark pull request #15582: [SPARK-18045][SQL][TESTS] Move `HiveDataFrameAnal...
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[GitHub] spark issue #14957: [SPARK-4502][SQL]Support parquet nested struct pruning a...
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[GitHub] spark issue #15354: [SPARK-17764][SQL] Add `to_json` supporting to convert n...
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[GitHub] spark issue #14957: [SPARK-4502][SQL]Support parquet nested struct pruning a...
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[GitHub] spark issue #15354: [SPARK-17764][SQL] Add `to_json` supporting to convert n...
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[GitHub] spark issue #15582: [SPARK-18045][SQL][TESTS] Move `HiveDataFrameAnalyticsSu...
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[GitHub] spark issue #14957: [SPARK-4502][SQL]Support parquet nested struct pruning a...
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