[GitHub] [spark] AmplabJenkins removed a comment on issue #24779: [SPARK-27929][SQL] Make percentile function receive frq of double

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[GitHub] [spark] SparkQA commented on issue #24297: [SPARK-27299][GRAPH][WIP] Spark Graph API design proposal

2019-06-12 Thread GitBox
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[GitHub] [spark] AmplabJenkins commented on issue #24851: [SPARK-27303][GRAPH] Add PropertyGraph construction API

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[GitHub] [spark] SparkQA commented on issue #24792: [SPARK-27943][SPARK-27953][SQL] Add new feature create table could specify column with default constraint

2019-06-12 Thread GitBox
SparkQA commented on issue #24792: [SPARK-27943][SPARK-27953][SQL] Add new 
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[GitHub] [spark] AmplabJenkins removed a comment on issue #24792: [SPARK-27943][SPARK-27953][SQL] Add new feature create table could specify column with default constraint

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[GitHub] [spark] SparkQA removed a comment on issue #24792: [SPARK-27943][SPARK-27953][SQL] Add new feature create table could specify column with default constraint

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[GitHub] [spark] SparkQA commented on issue #24850: [WIP][SPARK-28020][SQL][TEST] Port date.sql

2019-06-12 Thread GitBox
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[GitHub] [spark] AmplabJenkins removed a comment on issue #24849: [SPARK-28018][SQL] Allow upcasting decimal to double/float

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[GitHub] [spark] SparkQA commented on issue #24297: [SPARK-27299][GRAPH][WIP] Spark Graph API design proposal

2019-06-12 Thread GitBox
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[GitHub] [spark] AmplabJenkins removed a comment on issue #24792: [SPARK-27943][SPARK-27953][SQL] Add new feature create table could specify column with default constraint

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[GitHub] [spark] AmplabJenkins removed a comment on issue #24792: [SPARK-27943][SPARK-27953][SQL] Add new feature create table could specify column with default constraint

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[GitHub] [spark] SparkQA commented on issue #24792: [SPARK-27943][SPARK-27953][SQL] Add new feature create table could specify column with default constraint

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[GitHub] [spark] SparkQA commented on issue #24779: [SPARK-27929][SQL] Make percentile function receive frq of double

2019-06-12 Thread GitBox
SparkQA commented on issue #24779: [SPARK-27929][SQL] Make percentile function 
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[GitHub] [spark] ketank-new commented on a change in pull request #24788: [SPARK-26985][CORE] Fix "access only some column of the all of columns " for big endian architecture

2019-06-12 Thread GitBox
ketank-new commented on a change in pull request #24788: [SPARK-26985][CORE] 
Fix "access only some column of the all of columns " for big endian architecture
URL: https://github.com/apache/spark/pull/24788#discussion_r292885145
 
 

 ##
 File path: docs/sql-migration-guide-upgrade.md
 ##
 @@ -23,6 +23,7 @@ license: |
 {:toc}
 
 ## Upgrading From Spark SQL 2.4 to 3.0
+  - In Spark version 2.4 and earlier, SQL queries such as `FROM ` or 
`FROM  UNION ALL FROM ` are supported by accident. In hive-style 
`FROM  SELECT `, the `SELECT` clause is not negligible. Neither 
Hive nor Presto support this syntax. Therefore we will treat these queries as 
invalid since Spark 3.0.
 
 Review comment:
   yes .. looks like .. i better open a new PR


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[GitHub] [spark] AmplabJenkins removed a comment on issue #24829: [WIP][SPARK-27988][SQL][TEST] Port AGGREGATES.sql [Part 3]

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[GitHub] [spark] AmplabJenkins removed a comment on issue #24850: [WIP][SPARK-28020][SQL][TEST] Port date.sql

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[GitHub] [spark] AmplabJenkins commented on issue #24297: [SPARK-27299][GRAPH][WIP] Spark Graph API design proposal

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[GitHub] [spark] s1ck commented on issue #24851: [SPARK-27303][GRAPH] Add PropertyGraph construction API

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   @mengxr @gatorsmile Would be great to get some feedback from you. Thanks.


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[GitHub] [spark] SparkQA removed a comment on issue #24829: [WIP][SPARK-27988][SQL][TEST] Port AGGREGATES.sql [Part 3]

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[GitHub] [spark] SparkQA commented on issue #24788: [SPARK-26985][CORE] Fix "access only some column of the all of columns " for big endian architecture

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[GitHub] [spark] SparkQA commented on issue #23850: [SPARK-26949][SS] Prevent 'purge' to remove needed batch files in CompactibleFileStreamLog

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[GitHub] [spark] AmplabJenkins commented on issue #24779: [SPARK-27929][SQL] Make percentile function receive frq of double

2019-06-12 Thread GitBox
AmplabJenkins commented on issue #24779: [SPARK-27929][SQL] Make percentile 
function receive frq of double
URL: https://github.com/apache/spark/pull/24779#issuecomment-501245330
 
 
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[GitHub] [spark] SparkQA removed a comment on issue #24779: [SPARK-27929][SQL] Make percentile function receive frq of double

2019-06-12 Thread GitBox
SparkQA removed a comment on issue #24779: [SPARK-27929][SQL] Make percentile 
function receive frq of double
URL: https://github.com/apache/spark/pull/24779#issuecomment-501188256
 
 
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[GitHub] [spark] SparkQA removed a comment on issue #24852: [SPARK-28027][SQL] Add bitwise shift left/right operators

2019-06-12 Thread GitBox
SparkQA removed a comment on issue #24852: [SPARK-28027][SQL] Add bitwise shift 
left/right operators
URL: https://github.com/apache/spark/pull/24852#issuecomment-501293697
 
 
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[GitHub] [spark] AmplabJenkins removed a comment on issue #24852: [SPARK-28027][SQL] Add bitwise shift left/right operators

2019-06-12 Thread GitBox
AmplabJenkins removed a comment on issue #24852: [SPARK-28027][SQL] Add bitwise 
shift left/right operators
URL: https://github.com/apache/spark/pull/24852#issuecomment-501329536
 
 
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[GitHub] [spark] srowen commented on a change in pull request #24702: [SPARK-27989] [Kubernetes] [Core] Added retries on the connection to the driver for k8s

2019-06-12 Thread GitBox
srowen commented on a change in pull request #24702: [SPARK-27989] [Kubernetes] 
[Core] Added retries on the connection to the driver for k8s
URL: https://github.com/apache/spark/pull/24702#discussion_r292983218
 
 

 ##
 File path: 
core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala
 ##
 @@ -283,7 +283,12 @@ private[spark] object CoarseGrainedExecutorBackend 
extends Logging {
 executorConf,
 new SecurityManager(executorConf),
 clientMode = true)
-  val driver = fetcher.setupEndpointRefByURI(arguments.driverUrl)
+
+val driver = retry(3) {
+  fetcher.setupEndpointRefByURI(arguments.driverUrl)
+}
 
 Review comment:
   Oops @jlpedrosa I meant to retain the condition in the loop, but otherwise I 
find the code right above simpler. However I like retaining the original 
exception. Just please pay attention to the style. `driver = ` indent is off 
and needs to say `if (i == nTries - 1)`


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[GitHub] [spark] srowen commented on a change in pull request #24702: [SPARK-27989] [Kubernetes] [Core] Added retries on the connection to the driver for k8s

2019-06-12 Thread GitBox
srowen commented on a change in pull request #24702: [SPARK-27989] [Kubernetes] 
[Core] Added retries on the connection to the driver for k8s
URL: https://github.com/apache/spark/pull/24702#discussion_r292983407
 
 

 ##
 File path: 
resource-managers/kubernetes/docker/src/main/dockerfiles/spark/Dockerfile
 ##
 @@ -51,6 +51,8 @@ ENV SPARK_HOME /opt/spark
 
 WORKDIR /opt/spark/work-dir
 RUN chmod g+w /opt/spark/work-dir
+#Disable negative dns reslolution 
https://docs.oracle.com/javase/8/docs/technotes/guides/net/properties.html
+RUN sed -i -e 
's/networkaddress.cache.negative.ttl=10/networkaddress.cache.negative.ttl=0/g'  
/usr/lib/jvm/java-1.8-openjdk/jre/lib/security/java.security
 
 Review comment:
   I just wouldn't make this change here.


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[GitHub] [spark] AmplabJenkins removed a comment on issue #24852: [SPARK-28027][SQL] Add bitwise shift left/right operators

2019-06-12 Thread GitBox
AmplabJenkins removed a comment on issue #24852: [SPARK-28027][SQL] Add bitwise 
shift left/right operators
URL: https://github.com/apache/spark/pull/24852#issuecomment-501329554
 
 
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[GitHub] [spark] maryannxue commented on a change in pull request #24706: [SPARK-23128][SQL] A new approach to do adaptive execution in Spark SQL

2019-06-12 Thread GitBox
maryannxue commented on a change in pull request #24706: [SPARK-23128][SQL] A 
new approach to do adaptive execution in Spark SQL
URL: https://github.com/apache/spark/pull/24706#discussion_r292994737
 
 

 ##
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/AdaptiveSparkPlanExec.scala
 ##
 @@ -0,0 +1,446 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.adaptive
+
+import java.util
+import java.util.concurrent.LinkedBlockingQueue
+
+import scala.collection.JavaConverters._
+import scala.collection.concurrent.TrieMap
+import scala.collection.mutable
+import scala.concurrent.ExecutionContext
+
+import org.apache.spark.SparkException
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.Attribute
+import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, ReturnAnswer}
+import org.apache.spark.sql.catalyst.rules.{Rule, RuleExecutor}
+import org.apache.spark.sql.execution._
+import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec._
+import org.apache.spark.sql.execution.exchange._
+import 
org.apache.spark.sql.execution.ui.SparkListenerSQLAdaptiveExecutionUpdate
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.util.ThreadUtils
+
+/**
+ * A root node to execute the query plan adaptively. It splits the query plan 
into independent
+ * stages and executes them in order according to their dependencies. The 
query stage
+ * materializes its output at the end. When one stage completes, the data 
statistics of the
+ * materialized output will be used to optimize the remainder of the query.
+ *
+ * To create query stages, we traverse the query tree bottom up. When we hit 
an exchange node,
+ * and if all the child query stages of this exchange node are materialized, 
we create a new
+ * query stage for this exchange node. The new stage is then materialized 
asynchronously once it
+ * is created.
+ *
+ * When one query stage finishes materialization, the rest query is 
re-optimized and planned based
+ * on the latest statistics provided by all materialized stages. Then we 
traverse the query plan
+ * again and create more stages if possible. After all stages have been 
materialized, we execute
+ * the rest of the plan.
+ */
+case class AdaptiveSparkPlanExec(
+initialPlan: SparkPlan,
+@transient session: SparkSession,
+@transient subqueryMap: Map[Long, ExecSubqueryExpression],
+@transient stageCache: TrieMap[SparkPlan, QueryStageExec])
+  extends LeafExecNode {
+
+  @transient private val executionId = Option(
+
session.sparkContext.getLocalProperty(SQLExecution.EXECUTION_ID_KEY)).map(_.toLong)
+
+  @transient private val lock = new Object()
+
+  // The logical plan optimizer for re-optimizing the current logical plan.
+  @transient private val optimizer = new RuleExecutor[LogicalPlan] {
+// TODO add more optimization rules
+override protected def batches: Seq[Batch] = Seq()
+  }
+
+  // A list of physical plan rules to be applied before creation of query 
stages. The physical
+  // plan should reach a final status of query stages (i.e., no more addition 
or removal of
+  // Exchange nodes) after running these rules.
+  @transient private val queryStagePreparationRules: Seq[Rule[SparkPlan]] = 
Seq(
+PlanAdaptiveSubqueries(subqueryMap),
+EnsureRequirements(conf)
+  )
+
+  // A list of physical optimizer rules to be applied to a new stage before 
its execution. These
+  // optimizations should be stage-independent.
+  @transient private val queryStageOptimizerRules: Seq[Rule[SparkPlan]] = Seq(
+CollapseCodegenStages(conf)
+  )
+
+  private var currentStageId = 0
+
+  @volatile private var currentPhysicalPlan = initialPlan
+
+  @volatile private var isFinalPlan = false
+
+  @volatile private var fallback = false
+
+  /**
+   * Return type for `createQueryStages`
+   * @param newPlan the new plan with created query stages.
+   * @param allChildStagesMaterialized whether all child stages have been 
materialized.
+   * @param newStages the newly created query stages, including new reused 

[GitHub] [spark] dongjoon-hyun commented on a change in pull request #24851: [SPARK-27303][GRAPH] Add PropertyGraph construction API

2019-06-12 Thread GitBox
dongjoon-hyun commented on a change in pull request #24851: 
[SPARK-27303][GRAPH] Add PropertyGraph construction API
URL: https://github.com/apache/spark/pull/24851#discussion_r292997721
 
 

 ##
 File path: 
graph/api/src/test/java/org/apache/spark/graph/api/JavaPropertyGraphSuite.java
 ##
 @@ -0,0 +1,90 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.graph.api;
+
+import com.google.common.collect.Lists;
+import com.google.common.collect.Sets;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.RowFactory;
+import org.apache.spark.sql.test.TestSparkSession;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+import org.junit.After;
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Test;
+
+import java.io.Serializable;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.List;
+
+public abstract class JavaPropertyGraphSuite implements Serializable {
+private transient TestSparkSession spark;
+private transient CypherSession cypherSession = null;
+
+@Before
+public void setUp() {
+spark = new TestSparkSession();
+}
+
+@After
+public void tearDown() {
+spark.stop();
+spark = null;
+}
+
+@Test
+public void testCreateFromNodeFrame() {
+StructType personSchema = createSchema(
+Lists.newArrayList("id", "name"),
+Lists.newArrayList(DataTypes.LongType, DataTypes.StringType));
+
+List personData = Arrays.asList(
+RowFactory.create(0L, "Alice"),
+RowFactory.create(1L, "Bob"));
+
+StructType knowsSchema = createSchema(
+Lists.newArrayList("id", "source", "target", "since"),
+Lists.newArrayList(DataTypes.LongType, DataTypes.LongType, 
DataTypes.LongType, DataTypes.IntegerType));
+
+List knowsData = Collections.singletonList(RowFactory.create(0L, 
0L, 1L, 1984));
+
+Dataset personDf = spark.createDataFrame(personData, 
personSchema);
+NodeFrame personNodeFrame = NodeFrame.create(personDf, "id", 
Sets.newHashSet("Person"));
+
+Dataset knowsDf = spark.createDataFrame(knowsData, knowsSchema);
+RelationshipFrame knowsRelFrame = RelationshipFrame.create(knowsDf, 
"id", "source", "target", "KNOWS");
+
+PropertyGraph graph = 
cypherSession.createGraph(Lists.newArrayList(personNodeFrame), 
Lists.newArrayList(knowsRelFrame));
+List result = graph.nodes().collectAsList();
+Assert.assertEquals(1, result.size());
+}
+
+private StructType createSchema(List fieldNames, List 
dataTypes) {
+List fields = new ArrayList<>();
+for (int i = 0; i < fieldNames.size(); i++) {
+fields.add(DataTypes.createStructField(fieldNames.get(i), 
dataTypes.get(i), true));
+}
+return DataTypes.createStructType(fields);
+}
+}
 
 Review comment:
   FYI, Apache Spark uses 2-space indentation for Java code, too. Please fix 
this one and consider that in the next PRs.
   


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[GitHub] [spark] SparkQA commented on issue #24855: [SPARK-28030] convert filePath to URI in binary file data source

2019-06-12 Thread GitBox
SparkQA commented on issue #24855: [SPARK-28030] convert filePath to URI in 
binary file data source
URL: https://github.com/apache/spark/pull/24855#issuecomment-501345556
 
 
   **[Test build #106428 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/106428/testReport)**
 for PR 24855 at commit 
[`cf96785`](https://github.com/apache/spark/commit/cf96785ca77839ff92b7d9be1ccb67fb009be04b).


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[GitHub] [spark] SparkQA commented on issue #24854: [SPARK-28031][PySpark][TEST] Improve doctest on over function of Column

2019-06-12 Thread GitBox
SparkQA commented on issue #24854: [SPARK-28031][PySpark][TEST] Improve doctest 
on over function of Column
URL: https://github.com/apache/spark/pull/24854#issuecomment-501345557
 
 
   **[Test build #106429 has 
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 for PR 24854 at commit 
[`6afd936`](https://github.com/apache/spark/commit/6afd9362b597576e40860327a771fadcc9269078).


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[GitHub] [spark] SparkQA commented on issue #24706: [SPARK-23128][SQL] A new approach to do adaptive execution in Spark SQL

2019-06-12 Thread GitBox
SparkQA commented on issue #24706: [SPARK-23128][SQL] A new approach to do 
adaptive execution in Spark SQL
URL: https://github.com/apache/spark/pull/24706#issuecomment-501345570
 
 
   **[Test build #106430 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/106430/testReport)**
 for PR 24706 at commit 
[`ec59f88`](https://github.com/apache/spark/commit/ec59f882cf0b75fba7a4e0c0521db2ab9075f9f2).


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[GitHub] [spark] arunmahadevan commented on issue #23576: [SPARK-26655] [SS] Support multiple aggregates in append mode

2019-06-12 Thread GitBox
arunmahadevan commented on issue #23576: [SPARK-26655] [SS] Support multiple 
aggregates in append mode
URL: https://github.com/apache/spark/pull/23576#issuecomment-501348243
 
 
   Output watermark can be computed as some function of input watermark and the 
timestamp of events at that operator (e.g. min(input watermarks, timestamps of 
oldest event at that node)) so we could compute the other by storing only the 
input watermark. For now, we require the user to provide a timestamp column + 
lag using “withWatermark()” before each aggregate operation. 
   E.g. 
   ```
   input.
   .withWatermark("inputtime",...)
   .groupBy(window(...))
   .select($"window1.end".as("windowtime")
   .withWatermark("windowtime")..
   .groupBy(...)...
   ```
   Here the window.end of the first groupBy is the output watermark which 
becomes the input watermark of the second groupBy.
   
   Also note that the input water mark of an operator is propagated to the next 
operator only in the next batch so that it processes the events first and then 
the watermark.
   
   Let me know the specific cases where you found issues.


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[GitHub] [spark] holdenk commented on a change in pull request #24855: [SPARK-28030] convert filePath to URI in binary file data source

2019-06-12 Thread GitBox
holdenk commented on a change in pull request #24855: [SPARK-28030] convert 
filePath to URI in binary file data source
URL: https://github.com/apache/spark/pull/24855#discussion_r293003817
 
 

 ##
 File path: 
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/binaryfile/BinaryFileFormatSuite.scala
 ##
 @@ -368,4 +368,14 @@ class BinaryFileFormatSuite extends QueryTest with 
SharedSQLContext with SQLTest
   assert(caught.getMessage.contains("exceeds the max length allowed"))
 }
   }
+
+  test("SPARK-28030: support chars in file names that require URL encoding") {
+withTempDir { dir =>
+  val file = new File(dir, "test space.txt")
+  val content = "123".getBytes
+  Files.write(file.toPath, content, StandardOpenOption.CREATE, 
StandardOpenOption.WRITE)
+  val df = spark.read.format(BINARY_FILE).load(dir.getPath)
+  df.collect()
 
 Review comment:
   Maybe it would be good to assert that we get the bytes back, just in case 
it's skipping the files with space or something.


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[GitHub] [spark] holdenk commented on a change in pull request #24855: [SPARK-28030] convert filePath to URI in binary file data source

2019-06-12 Thread GitBox
holdenk commented on a change in pull request #24855: [SPARK-28030] convert 
filePath to URI in binary file data source
URL: https://github.com/apache/spark/pull/24855#discussion_r293004219
 
 

 ##
 File path: 
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/binaryfile/BinaryFileFormatSuite.scala
 ##
 @@ -368,4 +368,14 @@ class BinaryFileFormatSuite extends QueryTest with 
SharedSQLContext with SQLTest
   assert(caught.getMessage.contains("exceeds the max length allowed"))
 }
   }
+
+  test("SPARK-28030: support chars in file names that require URL encoding") {
+withTempDir { dir =>
 
 Review comment:
   Is it ok that we only have the space in the file name, or do we need it in 
the path were providing to trigger SPARK-28030?


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[GitHub] [spark] holdenk commented on a change in pull request #24855: [SPARK-28030] convert filePath to URI in binary file data source

2019-06-12 Thread GitBox
holdenk commented on a change in pull request #24855: [SPARK-28030] convert 
filePath to URI in binary file data source
URL: https://github.com/apache/spark/pull/24855#discussion_r293006022
 
 

 ##
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileScanRDD.scala
 ##
 @@ -38,7 +38,7 @@ import org.apache.spark.util.NextIterator
  * that need to be prepended to each row.
  *
  * @param partitionValues value of partition columns to be prepended to each 
row.
- * @param filePath path of the file to read
 
 Review comment:
   nit: Maybe add a comment here that we throw an exception if were passed an 
invalid URI.


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[GitHub] [spark] holdenk commented on a change in pull request #24855: [SPARK-28030] convert filePath to URI in binary file data source

2019-06-12 Thread GitBox
holdenk commented on a change in pull request #24855: [SPARK-28030] convert 
filePath to URI in binary file data source
URL: https://github.com/apache/spark/pull/24855#discussion_r293004966
 
 

 ##
 File path: 
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/binaryfile/BinaryFileFormatSuite.scala
 ##
 @@ -368,4 +368,14 @@ class BinaryFileFormatSuite extends QueryTest with 
SharedSQLContext with SQLTest
   assert(caught.getMessage.contains("exceeds the max length allowed"))
 }
   }
+
+  test("SPARK-28030: support chars in file names that require URL encoding") {
 
 Review comment:
   The change seems to impact not just the binary file format, maybe this 
belongs in one of our root datasource tests. What do you think?


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[GitHub] [spark] WangGuangxin commented on a change in pull request #24043: [SPARK-11412][SQL] Support merge schema for ORC

2019-06-12 Thread GitBox
WangGuangxin commented on a change in pull request #24043: [SPARK-11412][SQL] 
Support merge schema for ORC
URL: https://github.com/apache/spark/pull/24043#discussion_r293006575
 
 

 ##
 File path: 
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/ReadSchemaSuite.scala
 ##
 @@ -134,6 +135,31 @@ class VectorizedOrcReadSchemaSuite
   }
 }
 
+class MergedOrcReadSchemaSuite
+  extends ReadSchemaSuite
+  with AddColumnIntoTheMiddleTest
+  with HideColumnInTheMiddleTest
+  with AddNestedColumnTest
+  with HideNestedColumnTest
+  with ChangePositionTest
+  with BooleanTypeTest
+  with IntegralTypeTest
+  with ToDoubleTypeTest {
+
+  override val format: String = "orc"
+
 
 Review comment:
   done


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[GitHub] [spark] AmplabJenkins commented on issue #24854: [SPARK-28031][PySpark][TEST] Improve doctest on over function of Column

2019-06-12 Thread GitBox
AmplabJenkins commented on issue #24854: [SPARK-28031][PySpark][TEST] Improve 
doctest on over function of Column
URL: https://github.com/apache/spark/pull/24854#issuecomment-501357776
 
 
   Test PASSed.
   Refer to this link for build results (access rights to CI server needed): 
   https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/106429/
   Test PASSed.


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[GitHub] [spark] AmplabJenkins commented on issue #24854: [SPARK-28031][PySpark][TEST] Improve doctest on over function of Column

2019-06-12 Thread GitBox
AmplabJenkins commented on issue #24854: [SPARK-28031][PySpark][TEST] Improve 
doctest on over function of Column
URL: https://github.com/apache/spark/pull/24854#issuecomment-501357769
 
 
   Merged build finished. Test PASSed.


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[GitHub] [spark] zsxwing commented on issue #24833: [SPARK-27979][BUILD][test-maven] Remove deprecated `--force` option in `build/mvn` and `run-tests.py`

2019-06-12 Thread GitBox
zsxwing commented on issue #24833: [SPARK-27979][BUILD][test-maven] Remove 
deprecated `--force` option in `build/mvn` and `run-tests.py`
URL: https://github.com/apache/spark/pull/24833#issuecomment-501363039
 
 
   @srowen @dongjoon-hyun could you also fix the jenkins job since it's broken 
by this PR? 
   
   
https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Compile/job/spark-master-compile-maven-hadoop-2.7/
   
   ```
   Unable to parse command line options: Unrecognized option: --force
   ```


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[GitHub] [spark] AmplabJenkins removed a comment on issue #24857: [CORE] Remove an unused variable in SparkSubmt.scala

2019-06-12 Thread GitBox
AmplabJenkins removed a comment on issue #24857: [CORE] Remove an unused 
variable in SparkSubmt.scala
URL: https://github.com/apache/spark/pull/24857#issuecomment-501364955
 
 
   Can one of the admins verify this patch?


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[GitHub] [spark] AmplabJenkins commented on issue #24857: [CORE] Remove an unused variable in SparkSubmt.scala

2019-06-12 Thread GitBox
AmplabJenkins commented on issue #24857: [CORE] Remove an unused variable in 
SparkSubmt.scala
URL: https://github.com/apache/spark/pull/24857#issuecomment-501366199
 
 
   Can one of the admins verify this patch?


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[GitHub] [spark] dongjoon-hyun commented on a change in pull request #24842: [SPARK-28002][SQL] Support WITH clause column aliases

2019-06-12 Thread GitBox
dongjoon-hyun commented on a change in pull request #24842: [SPARK-28002][SQL] 
Support WITH clause column aliases
URL: https://github.com/apache/spark/pull/24842#discussion_r293025899
 
 

 ##
 File path: 
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
 ##
 @@ -633,4 +634,16 @@ class AnalysisSuite extends AnalysisTest with Matchers {
 val res = ViewAnalyzer.execute(view)
 comparePlans(res, expected)
   }
+
+  test("SPARK-28002: CTE with non-existing column alias") {
+assertAnalysisError(parsePlan("WITH t(x) AS (SELECT 1) SELECT * FROM t 
WHERE y = 1"),
+  Seq("cannot resolve '`y`' given input columns: [x]"))
+  }
+
+  test("SPARK-28002: CTE with non-matching column alias") {
+assertAnalysisError(parsePlan("WITH t(x, y) AS (SELECT 1) SELECT * FROM t 
WHERE x = 1"),
+  Seq("Number of column aliases does not match number of columns. Number 
of column aliases: " +
+"2; number of columns: 1."))
+  }
+
 
 Review comment:
   nit. remove empty line.


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[GitHub] [spark] srowen commented on issue #24833: [SPARK-27979][BUILD][test-maven] Remove deprecated `--force` option in `build/mvn` and `run-tests.py`

2019-06-12 Thread GitBox
srowen commented on issue #24833: [SPARK-27979][BUILD][test-maven] Remove 
deprecated `--force` option in `build/mvn` and `run-tests.py`
URL: https://github.com/apache/spark/pull/24833#issuecomment-501374904
 
 
   Oh, nevermind. The _compile_ job failed and I hadn't updated that. I had 
updates the _test_ jobs previously. I don't think anything was overwritten. OK, 
should be OK now unless I'm missing more master jobs.


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[GitHub] [spark] BryanCutler commented on a change in pull request #24844: [SPARK-28003][PYTHON] Allow NaT values when creating Spark dataframe from pandas with Arrow

2019-06-12 Thread GitBox
BryanCutler commented on a change in pull request #24844: [SPARK-28003][PYTHON] 
Allow NaT values when creating Spark dataframe from pandas with Arrow
URL: https://github.com/apache/spark/pull/24844#discussion_r293034013
 
 

 ##
 File path: python/pyspark/serializers.py
 ##
 @@ -296,7 +296,7 @@ def create_array(s, t):
 mask = s.isnull()
 # Ensure timestamp series are in expected form for Spark internal 
representation
 if t is not None and pa.types.is_timestamp(t):
-s = _check_series_convert_timestamps_internal(s.fillna(0), 
self._timezone)
+s = _check_series_convert_timestamps_internal(s, 
self._timezone)
 
 Review comment:
   I believe it was due to a Pandas error, most likely because we were testing 
with 0.19.2 at the time. Can you manually run some tests with different Pandas 
versions? It will be best to test with older versions, but it might be kind of 
hard to get 0.19.2 working with pyarrow 0.12.1 though..


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[GitHub] [spark] BryanCutler commented on a change in pull request #24844: [SPARK-28003][PYTHON] Allow NaT values when creating Spark dataframe from pandas with Arrow

2019-06-12 Thread GitBox
BryanCutler commented on a change in pull request #24844: [SPARK-28003][PYTHON] 
Allow NaT values when creating Spark dataframe from pandas with Arrow
URL: https://github.com/apache/spark/pull/24844#discussion_r293038513
 
 

 ##
 File path: python/pyspark/sql/tests/test_arrow.py
 ##
 @@ -383,6 +383,19 @@ def test_timestamp_dst(self):
 assert_frame_equal(pdf, df_from_python.toPandas())
 assert_frame_equal(pdf, df_from_pandas.toPandas())
 
+def test_timestamp_nat(self):
+import pandas as pd
+dt1 = [pd.NaT, pd.Timestamp('2019-06-11')] * 100
+dt2 = [None, pd.Timestamp('2019-06-11')] * 100
+pdf1 = pd.DataFrame({'time': dt1})
+pdf2 = pd.DataFrame({'time': dt2})
+
+df1 = self.spark.createDataFrame(pdf1)
+df2 = self.spark.createDataFrame(pdf2)
 
 Review comment:
   I think you can just combine these to 1 DataFrame, but I think it would be 
good to also check against toPandas without Arrow


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[GitHub] [spark] gatorsmile commented on a change in pull request #24706: [SPARK-23128][SQL] A new approach to do adaptive execution in Spark SQL

2019-06-12 Thread GitBox
gatorsmile commented on a change in pull request #24706: [SPARK-23128][SQL] A 
new approach to do adaptive execution in Spark SQL
URL: https://github.com/apache/spark/pull/24706#discussion_r292898739
 
 

 ##
 File path: 
sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala
 ##
 @@ -0,0 +1,275 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.adaptive
+
+import org.apache.spark.sql.QueryTest
+import org.apache.spark.sql.execution.{ReusedSubqueryExec, SparkPlan}
+import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, 
SortMergeJoinExec}
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.test.SharedSQLContext
+
+class AdaptiveQueryExecSuite extends QueryTest with SharedSQLContext {
+
+  setupTestData()
+
+  private def runAdaptiveAndVerifyResult(query: String): (SparkPlan, 
SparkPlan) = {
+val dfAdaptive = sql(query)
+val result = dfAdaptive.collect()
+withSQLConf(SQLConf.RUNTIME_REOPTIMIZATION_ENABLED.key -> "false") {
+  val df = sql(query)
+  QueryTest.sameRows(result.toSeq, df.collect().toSeq)
+}
+val plan = dfAdaptive.queryExecution.executedPlan
+assert(plan.isInstanceOf[AdaptiveSparkPlanExec])
+val adaptivePlan = plan.asInstanceOf[AdaptiveSparkPlanExec].executedPlan
+(dfAdaptive.queryExecution.sparkPlan, adaptivePlan)
+  }
+
+  private def findTopLevelBroadcastHashJoin(plan: SparkPlan): 
Seq[BroadcastHashJoinExec] = {
+plan.collect {
+  case j: BroadcastHashJoinExec => Seq(j)
+  case s: QueryStageExec => findTopLevelBroadcastHashJoin(s.plan)
+}.flatten
+  }
+
+  private def findTopLevelSortMergeJoin(plan: SparkPlan): 
Seq[SortMergeJoinExec] = {
+plan.collect {
+  case j: SortMergeJoinExec => Seq(j)
+  case s: QueryStageExec => findTopLevelSortMergeJoin(s.plan)
+}.flatten
+  }
+
+  private def findReusedExchange(plan: SparkPlan): Seq[ReusedQueryStageExec] = 
{
+plan.collect {
+  case e: ReusedQueryStageExec => Seq(e)
+  case a: AdaptiveSparkPlanExec => findReusedExchange(a.executedPlan)
+  case s: QueryStageExec => findReusedExchange(s.plan)
+  case p: SparkPlan => p.subqueries.flatMap(findReusedExchange)
+}.flatten
+  }
+
+  private def findReusedSubquery(plan: SparkPlan): Seq[ReusedSubqueryExec] = {
+plan.collect {
+  case e: ReusedSubqueryExec => Seq(e)
+  case s: QueryStageExec => findReusedSubquery(s.plan)
+  case p: SparkPlan => p.subqueries.flatMap(findReusedSubquery)
+}.flatten
+  }
+
+  test("Change merge join to broadcast join") {
+withSQLConf(
+SQLConf.RUNTIME_REOPTIMIZATION_ENABLED.key -> "true",
+SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "80") {
+  val (plan, adaptivePlan) = runAdaptiveAndVerifyResult(
+"SELECT * FROM testData join testData2 ON key = a where value = '1'")
 
 Review comment:
   ```Scala
   withSQLConf(
   SQLConf.RUNTIME_REOPTIMIZATION_ENABLED.key -> "true",
   SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "80") {
 spark.sql(
   "SELECT * FROM testData join testData2 ON key = a where value = 
'1'").explain()
   }
   
   withSQLConf(
 SQLConf.RUNTIME_REOPTIMIZATION_ENABLED.key -> "false",
 SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "80") {
 spark.sql(
   "SELECT * FROM testData join testData2 ON key = a where value = 
'1'").explain()
   }
   ```
   
   Try these? It sounds like we are unable to tell the difference from the 
physical plans. Also, the WholeStage codegen ID is lost after we turn on the 
adaptive query execution.


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[GitHub] [spark] gatorsmile commented on a change in pull request #24706: [SPARK-23128][SQL] A new approach to do adaptive execution in Spark SQL

2019-06-12 Thread GitBox
gatorsmile commented on a change in pull request #24706: [SPARK-23128][SQL] A 
new approach to do adaptive execution in Spark SQL
URL: https://github.com/apache/spark/pull/24706#discussion_r292898739
 
 

 ##
 File path: 
sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala
 ##
 @@ -0,0 +1,275 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.adaptive
+
+import org.apache.spark.sql.QueryTest
+import org.apache.spark.sql.execution.{ReusedSubqueryExec, SparkPlan}
+import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, 
SortMergeJoinExec}
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.test.SharedSQLContext
+
+class AdaptiveQueryExecSuite extends QueryTest with SharedSQLContext {
+
+  setupTestData()
+
+  private def runAdaptiveAndVerifyResult(query: String): (SparkPlan, 
SparkPlan) = {
+val dfAdaptive = sql(query)
+val result = dfAdaptive.collect()
+withSQLConf(SQLConf.RUNTIME_REOPTIMIZATION_ENABLED.key -> "false") {
+  val df = sql(query)
+  QueryTest.sameRows(result.toSeq, df.collect().toSeq)
+}
+val plan = dfAdaptive.queryExecution.executedPlan
+assert(plan.isInstanceOf[AdaptiveSparkPlanExec])
+val adaptivePlan = plan.asInstanceOf[AdaptiveSparkPlanExec].executedPlan
+(dfAdaptive.queryExecution.sparkPlan, adaptivePlan)
+  }
+
+  private def findTopLevelBroadcastHashJoin(plan: SparkPlan): 
Seq[BroadcastHashJoinExec] = {
+plan.collect {
+  case j: BroadcastHashJoinExec => Seq(j)
+  case s: QueryStageExec => findTopLevelBroadcastHashJoin(s.plan)
+}.flatten
+  }
+
+  private def findTopLevelSortMergeJoin(plan: SparkPlan): 
Seq[SortMergeJoinExec] = {
+plan.collect {
+  case j: SortMergeJoinExec => Seq(j)
+  case s: QueryStageExec => findTopLevelSortMergeJoin(s.plan)
+}.flatten
+  }
+
+  private def findReusedExchange(plan: SparkPlan): Seq[ReusedQueryStageExec] = 
{
+plan.collect {
+  case e: ReusedQueryStageExec => Seq(e)
+  case a: AdaptiveSparkPlanExec => findReusedExchange(a.executedPlan)
+  case s: QueryStageExec => findReusedExchange(s.plan)
+  case p: SparkPlan => p.subqueries.flatMap(findReusedExchange)
+}.flatten
+  }
+
+  private def findReusedSubquery(plan: SparkPlan): Seq[ReusedSubqueryExec] = {
+plan.collect {
+  case e: ReusedSubqueryExec => Seq(e)
+  case s: QueryStageExec => findReusedSubquery(s.plan)
+  case p: SparkPlan => p.subqueries.flatMap(findReusedSubquery)
+}.flatten
+  }
+
+  test("Change merge join to broadcast join") {
+withSQLConf(
+SQLConf.RUNTIME_REOPTIMIZATION_ENABLED.key -> "true",
+SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "80") {
+  val (plan, adaptivePlan) = runAdaptiveAndVerifyResult(
+"SELECT * FROM testData join testData2 ON key = a where value = '1'")
 
 Review comment:
   ```Scala
   withSQLConf(
   SQLConf.RUNTIME_REOPTIMIZATION_ENABLED.key -> "true",
   SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "80") {
 spark.sql(
   "SELECT * FROM testData join testData2 ON key = a where value = 
'1'").explain()
   }
   
   withSQLConf(
 SQLConf.RUNTIME_REOPTIMIZATION_ENABLED.key -> "false",
 SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "80") {
 spark.sql(
   "SELECT * FROM testData join testData2 ON key = a where value = 
'1'").explain()
   }
   ```
   
   Try these? It sounds like the WholeStage codegen ID is lost after we turn on 
the adaptive query execution.


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[GitHub] [spark] dongjoon-hyun closed pull request #24847: [SPARK-28013][BUILD][SS] Upgrade to Kafka 2.2.1

2019-06-12 Thread GitBox
dongjoon-hyun closed pull request #24847: [SPARK-28013][BUILD][SS] Upgrade to 
Kafka 2.2.1
URL: https://github.com/apache/spark/pull/24847
 
 
   


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[GitHub] [spark] SparkQA commented on issue #24792: [SPARK-27943][SPARK-27953][SQL] Add new feature create table could specify column with default constraint

2019-06-12 Thread GitBox
SparkQA commented on issue #24792: [SPARK-27943][SPARK-27953][SQL] Add new 
feature create table could specify column with default constraint
URL: https://github.com/apache/spark/pull/24792#issuecomment-501307990
 
 
   **[Test build #106418 has 
finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/106418/testReport)**
 for PR 24792 at commit 
[`545bba0`](https://github.com/apache/spark/commit/545bba062649e3b23f0dcaa28592d017055be1cb).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.


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[GitHub] [spark] AmplabJenkins commented on issue #24706: [SPARK-23128][SQL] A new approach to do adaptive execution in Spark SQL

2019-06-12 Thread GitBox
AmplabJenkins commented on issue #24706: [SPARK-23128][SQL] A new approach to 
do adaptive execution in Spark SQL
URL: https://github.com/apache/spark/pull/24706#issuecomment-501318777
 
 
   Merged build finished. Test PASSed.


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[GitHub] [spark] AmplabJenkins commented on issue #24706: [SPARK-23128][SQL] A new approach to do adaptive execution in Spark SQL

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[GitHub] [spark] SparkQA commented on issue #24853: [WIP][SPARK-28029][SQL][TEST] Port int2.sql

2019-06-12 Thread GitBox
SparkQA commented on issue #24853: [WIP][SPARK-28029][SQL][TEST] Port int2.sql
URL: https://github.com/apache/spark/pull/24853#issuecomment-501323266
 
 
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[GitHub] [spark] AmplabJenkins commented on issue #24853: [WIP][SPARK-28029][SQL][TEST] Port int2.sql

2019-06-12 Thread GitBox
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[GitHub] [spark] AmplabJenkins commented on issue #24853: [WIP][SPARK-28029][SQL][TEST] Port int2.sql

2019-06-12 Thread GitBox
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[GitHub] [spark] wangyum commented on a change in pull request #24853: [WIP][SPARK-28029][SQL][TEST] Port int2.sql

2019-06-12 Thread GitBox
wangyum commented on a change in pull request #24853: 
[WIP][SPARK-28029][SQL][TEST] Port int2.sql
URL: https://github.com/apache/spark/pull/24853#discussion_r292972799
 
 

 ##
 File path: sql/core/src/test/resources/sql-tests/inputs/pgSQL/int2.sql
 ##
 @@ -0,0 +1,126 @@
+--
+-- Portions Copyright (c) 1996-2019, PostgreSQL Global Development Group
+--
+--
+-- INT2
+-- 
https://github.com/postgres/postgres/blob/REL_12_BETA1/src/test/regress/sql/int2.sql
+
+CREATE TABLE INT2_TBL(f1 smallint) USING parquet;
+
+-- [SPARK-28023] Trim the string when cast string type to other types
+INSERT INTO INT2_TBL VALUES (trim('0   '));
+
+INSERT INTO INT2_TBL VALUES (trim('  1234 '));
+
+INSERT INTO INT2_TBL VALUES (trim('-1234'));
+
+-- [SPARK-27923] Invalid input syntax for type short throws exception at 
PostgreSQL
+-- INSERT INTO INT2_TBL VALUES ('34.5');
+
+-- largest and smallest values
+INSERT INTO INT2_TBL VALUES ('32767');
+
+INSERT INTO INT2_TBL VALUES ('-32767');
+
+-- bad input values -- should give errors
+-- INSERT INTO INT2_TBL VALUES ('10');
+-- INSERT INTO INT2_TBL VALUES ('asdf');
+-- INSERT INTO INT2_TBL VALUES ('');
+-- INSERT INTO INT2_TBL VALUES ('- 1234');
+-- INSERT INTO INT2_TBL VALUES ('4 444');
+-- INSERT INTO INT2_TBL VALUES ('123 dt');
+-- INSERT INTO INT2_TBL VALUES ('');
+
+
+SELECT '' AS five, * FROM INT2_TBL;
+
+SELECT '' AS four, i.* FROM INT2_TBL i WHERE i.f1 <> smallint('0');
+
+SELECT '' AS four, i.* FROM INT2_TBL i WHERE i.f1 <> int('0');
+
+SELECT '' AS one, i.* FROM INT2_TBL i WHERE i.f1 = smallint('0');
+
+SELECT '' AS one, i.* FROM INT2_TBL i WHERE i.f1 = int('0');
+
+SELECT '' AS two, i.* FROM INT2_TBL i WHERE i.f1 < smallint('0');
+
+SELECT '' AS two, i.* FROM INT2_TBL i WHERE i.f1 < int('0');
+
+SELECT '' AS three, i.* FROM INT2_TBL i WHERE i.f1 <= smallint('0');
+
+SELECT '' AS three, i.* FROM INT2_TBL i WHERE i.f1 <= int('0');
+
+SELECT '' AS two, i.* FROM INT2_TBL i WHERE i.f1 > smallint('0');
+
+SELECT '' AS two, i.* FROM INT2_TBL i WHERE i.f1 > int('0');
+
+SELECT '' AS three, i.* FROM INT2_TBL i WHERE i.f1 >= smallint('0');
+
+SELECT '' AS three, i.* FROM INT2_TBL i WHERE i.f1 >= int('0');
+
+-- positive odds
+SELECT '' AS one, i.* FROM INT2_TBL i WHERE (i.f1 % smallint('2')) = 
smallint('1');
+
+-- any evens
+SELECT '' AS three, i.* FROM INT2_TBL i WHERE (i.f1 % int('2')) = 
smallint('0');
+
+-- [SPARK-28024] Incorrect value when out of range
+SELECT '' AS five, i.f1, i.f1 * smallint('2') AS x FROM INT2_TBL i;
+
+SELECT '' AS five, i.f1, i.f1 * smallint('2') AS x FROM INT2_TBL i
+WHERE abs(f1) < 16384;
+
+SELECT '' AS five, i.f1, i.f1 * int('2') AS x FROM INT2_TBL i;
+
+-- [SPARK-28024] Incorrect value when out of range
+SELECT '' AS five, i.f1, i.f1 + smallint('2') AS x FROM INT2_TBL i;
+
+SELECT '' AS five, i.f1, i.f1 + smallint('2') AS x FROM INT2_TBL i
+WHERE f1 < 32766;
+
+SELECT '' AS five, i.f1, i.f1 + int('2') AS x FROM INT2_TBL i;
+
+-- [SPARK-28024] Incorrect value when out of range
+SELECT '' AS five, i.f1, i.f1 - smallint('2') AS x FROM INT2_TBL i;
+
+SELECT '' AS five, i.f1, i.f1 - smallint('2') AS x FROM INT2_TBL i
+WHERE f1 > -32767;
+
+SELECT '' AS five, i.f1, i.f1 - int('2') AS x FROM INT2_TBL i;
+
+-- The result is different because [SPARK-2659]
+SELECT '' AS five, i.f1, i.f1 / smallint('2') AS x FROM INT2_TBL i;
+
+-- The result is different because [SPARK-2659]
+SELECT '' AS five, i.f1, i.f1 / int('2') AS x FROM INT2_TBL i;
+
+-- corner cases
+SELECT string(shiftleft(smallint(-1), 15));
+SELECT string(smallint(shiftleft(smallint(-1), 15))+1);
+
+-- check sane handling of INT16_MIN overflow cases
+-- [SPARK-28024] Incorrect numeric values when out of range
+-- SELECT smallint((-32768)) * smallint(-1);
+-- SELECT smallint(-32768) / smallint(-1);
+SELECT smallint(-32768) % smallint(-1);
+
+-- [SPARK-28028] Cast numeric to integral type need round
+-- check rounding when casting from float
+SELECT x, smallint(x) AS int2_value
+FROM (VALUES float(-2.5),
+ float(-1.5),
+ float(-0.5),
+ float(0.0),
+ float(0.5),
+ float(1.5),
+ float(2.5)) t(x);
+
+-- check rounding when casting from numeric
+SELECT x, smallint(x) AS int2_value
+FROM (VALUES decimal(-2.5),
 
 Review comment:
   We do not have `numeric` type, can we use `decimal`?


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[GitHub] [spark] SparkQA removed a comment on issue #23850: [SPARK-26949][SS] Prevent 'purge' to remove needed batch files in CompactibleFileStreamLog

2019-06-12 Thread GitBox
SparkQA removed a comment on issue #23850: [SPARK-26949][SS] Prevent 'purge' to 
remove needed batch files in CompactibleFileStreamLog
URL: https://github.com/apache/spark/pull/23850#issuecomment-501254287
 
 
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[GitHub] [spark] SparkQA commented on issue #24852: [SPARK-28027][SQL] Add bitwise shift left/right operators

2019-06-12 Thread GitBox
SparkQA commented on issue #24852: [SPARK-28027][SQL] Add bitwise shift 
left/right operators
URL: https://github.com/apache/spark/pull/24852#issuecomment-501329288
 
 
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* This patch **fails Spark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.


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[GitHub] [spark] AmplabJenkins commented on issue #24852: [SPARK-28027][SQL] Add bitwise shift left/right operators

2019-06-12 Thread GitBox
AmplabJenkins commented on issue #24852: [SPARK-28027][SQL] Add bitwise shift 
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URL: https://github.com/apache/spark/pull/24852#issuecomment-501329536
 
 
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[GitHub] [spark] AmplabJenkins commented on issue #24852: [SPARK-28027][SQL] Add bitwise shift left/right operators

2019-06-12 Thread GitBox
AmplabJenkins commented on issue #24852: [SPARK-28027][SQL] Add bitwise shift 
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URL: https://github.com/apache/spark/pull/24852#issuecomment-501329554
 
 
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[GitHub] [spark] SparkQA commented on issue #23850: [SPARK-26949][SS] Prevent 'purge' to remove needed batch files in CompactibleFileStreamLog

2019-06-12 Thread GitBox
SparkQA commented on issue #23850: [SPARK-26949][SS] Prevent 'purge' to remove 
needed batch files in CompactibleFileStreamLog
URL: https://github.com/apache/spark/pull/23850#issuecomment-501329684
 
 
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* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.


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[GitHub] [spark] wangyum closed pull request #24852: [SPARK-28027][SQL] Add bitwise shift left/right operators

2019-06-12 Thread GitBox
wangyum closed pull request #24852: [SPARK-28027][SQL] Add bitwise shift 
left/right operators
URL: https://github.com/apache/spark/pull/24852
 
 
   


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[GitHub] [spark] wangyum commented on issue #24852: [SPARK-28027][SQL] Add bitwise shift left/right operators

2019-06-12 Thread GitBox
wangyum commented on issue #24852: [SPARK-28027][SQL] Add bitwise shift 
left/right operators
URL: https://github.com/apache/spark/pull/24852#issuecomment-501335275
 
 
   Close it because it conflicts with the table definition:
   ```
   CREATE TABLE parquet_compat(
 col_0 ARRAY,
 col_1 ARRAY,
 col_2 ARRAY>
   ---^^^
   )
   ```
   
https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/106423/testReport/org.apache.spark.sql.hive/ParquetHiveCompatibilitySuite/array/


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[GitHub] [spark] WeichenXu123 commented on issue #24643: [SPARK-26412][PySpark][SQL] Allow Pandas UDF to take an iterator of pd.Series or an iterator of tuple of pd.Series

2019-06-12 Thread GitBox
WeichenXu123 commented on issue #24643: [SPARK-26412][PySpark][SQL] Allow 
Pandas UDF to take an iterator of pd.Series or an iterator of tuple of pd.Series
URL: https://github.com/apache/spark/pull/24643#issuecomment-501337363
 
 
   @meng Done. Leave doc which will update soon.


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