[GitHub] spark pull request #22130: [SPARK-25137][Spark Shell] NumberFormatException`...
GitHub user vinodkc opened a pull request: https://github.com/apache/spark/pull/22130 [SPARK-25137][Spark Shell] NumberFormatException` when starting spark-shell from Mac terminal ## What changes were proposed in this pull request? When starting spark-shell from Mac terminal, Getting exception [ERROR] Failed to construct terminal; falling back to unsupported java.lang.NumberFormatException: For input string: "0x100" at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65) at java.lang.Integer.parseInt(Integer.java:580) at java.lang.Integer.valueOf(Integer.java:766) at jline.internal.InfoCmp.parseInfoCmp(InfoCmp.java:59) at jline.UnixTerminal.parseInfoCmp(UnixTerminal.java:242) at jline.UnixTerminal.(UnixTerminal.java:65) at jline.UnixTerminal.(UnixTerminal.java:50) at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62) at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) at java.lang.reflect.Constructor.newInstance(Constructor.java:423) at java.lang.Class.newInstance(Class.java:442) at jline.TerminalFactory.getFlavor(TerminalFactory.java:211) This issue is due a jline defect : https://github.com/jline/jline2/issues/281, which is fixed in Jline 2.14.4, bumping up JLine version in spark to version > Jline 2.14.4 will fix the issue ## How was this patch tested? No new UT/automation test added, after upgrade to latest Jline version 2.14.6, manually tested spark shell features You can merge this pull request into a Git repository by running: $ git pull https://github.com/vinodkc/spark br_UpgradeJLineVersion Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/22130.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 #22130 commit d00929f28b2523869252d67fefc04297aadc5af6 Author: Vinod KC Date: 2018-08-17T04:10:18Z Upgrade JLine to 2.14.6 --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #22130: [SPARK-25137][Spark Shell] NumberFormatException` when s...
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[GitHub] spark issue #22121: [SPARK-25133][SQL][Doc]AVRO data source guide
Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/22121 @gengliangwang Could you also post the screen shot in your PR description? --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #22130: [SPARK-25137][Spark Shell] NumberFormatException` when s...
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[GitHub] spark pull request #21868: [SPARK-24906][SQL] Adaptively enlarge split / par...
Github user habren commented on a diff in the pull request:
https://github.com/apache/spark/pull/21868#discussion_r210793717
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/DataSourceScanExec.scala
---
@@ -425,12 +426,44 @@ case class FileSourceScanExec(
fsRelation: HadoopFsRelation): RDD[InternalRow] = {
val defaultMaxSplitBytes =
fsRelation.sparkSession.sessionState.conf.filesMaxPartitionBytes
-val openCostInBytes =
fsRelation.sparkSession.sessionState.conf.filesOpenCostInBytes
+var openCostInBytes =
fsRelation.sparkSession.sessionState.conf.filesOpenCostInBytes
val defaultParallelism =
fsRelation.sparkSession.sparkContext.defaultParallelism
val totalBytes = selectedPartitions.flatMap(_.files.map(_.getLen +
openCostInBytes)).sum
val bytesPerCore = totalBytes / defaultParallelism
-val maxSplitBytes = Math.min(defaultMaxSplitBytes,
Math.max(openCostInBytes, bytesPerCore))
+var maxSplitBytes = Math.min(defaultMaxSplitBytes,
Math.max(openCostInBytes, bytesPerCore))
+
+
if(fsRelation.sparkSession.sessionState.conf.isParquetSizeAdaptiveEnabled &&
+ (fsRelation.fileFormat.isInstanceOf[ParquetSource] ||
+fsRelation.fileFormat.isInstanceOf[OrcFileFormat])) {
+ if (relation.dataSchema.map(_.dataType).forall(dataType =>
+dataType.isInstanceOf[CalendarIntervalType] ||
dataType.isInstanceOf[StructType]
+ || dataType.isInstanceOf[MapType] ||
dataType.isInstanceOf[NullType]
+ || dataType.isInstanceOf[AtomicType] ||
dataType.isInstanceOf[ArrayType])) {
+
+def getTypeLength(dataType: DataType): Int = {
+ if (dataType.isInstanceOf[StructType]) {
+
fsRelation.sparkSession.sessionState.conf.parquetStructTypeLength
+ } else if (dataType.isInstanceOf[ArrayType]) {
+
fsRelation.sparkSession.sessionState.conf.parquetArrayTypeLength
+ } else if (dataType.isInstanceOf[MapType]) {
+fsRelation.sparkSession.sessionState.conf.parquetMapTypeLength
+ } else {
+dataType.defaultSize
+ }
+}
+
+val selectedColumnSize =
requiredSchema.map(_.dataType).map(getTypeLength(_))
+ .reduceOption(_ + _).getOrElse(StringType.defaultSize)
+val totalColumnSize =
relation.dataSchema.map(_.dataType).map(getTypeLength(_))
+ .reduceOption(_ + _).getOrElse(StringType.defaultSize)
--- End diff --
@gatorsmile The target of this change is not making users easy to set the
partition size. Instead, when user set the partition size, this change will try
its best to make sure the read size is close to the value that set by user.
Without this change, when user set partition size to 128MB, the actual read
size may be 1MB or even smaller because of column pruning.
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[GitHub] spark issue #21950: [SPARK-24914][SQL][WIP] Add configuration to avoid OOM d...
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[GitHub] spark issue #21537: [SPARK-24505][SQL] Convert strings in codegen to blocks:...
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/21537 It's a good point that we should have a design doc for this codegen infrastructure improvement, since it's very critical to Spark. And we should have it reviewed by the community. There were some discussions on the PRs and JIRAs, but it didn't happen in the dev list. This is something we should do next. At this stage, I think it's too late to revert anything related to the codegen improvement. There are so many codegen templates get touched and I think reverting is riskier. But we should hold it now until the design doc is reviewed by the community in dev list. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #22116: [DOCS]Update configuration.md
Github user KraFusion commented on the issue: https://github.com/apache/spark/pull/22116 @srowen Thanks! yes, my bad. next time I will bundle (better yet I will look for the same issue elsewhere in the docs), and I'll use a better title. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #21868: [SPARK-24906][SQL] Adaptively enlarge split / partition ...
Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/21868 @habren, BTW, just for clarification, you can set the bigger number to `spark.sql.files.maxPartitionBytes` explicitly and that resolved your issue. This one is to handle it dynamically, right? --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #22124: [SPARK-25135][SQL] Insert datasource table may al...
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22124#discussion_r210799343
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala
---
@@ -490,7 +490,8 @@ object DDLPreprocessingUtils {
case (expected, actual) =>
if (expected.dataType.sameType(actual.dataType) &&
expected.name == actual.name &&
- expected.metadata == actual.metadata) {
+ expected.metadata == actual.metadata &&
+ expected.exprId.id == actual.exprId.id) {
--- End diff --
why does this fix the problem?
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[GitHub] spark issue #22120: [SPARK-25131]Event logs missing applicationAttemptId for...
Github user ajithme commented on the issue: https://github.com/apache/spark/pull/22120 @vanzin I agree its a trivial change. Just wanted it to be consistent output with yarn cluster mode. This is not just for event logs also for a custom SparkListener , it may be confusing that appId is empty in client case and a actual number in cluster case for onApplicationStart, this is where its effect can be seen. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #22123: [SPARK-25134][SQL] Csv column pruning with checking of h...
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[GitHub] spark pull request #22126: [SPARK-23938][SQL][FOLLOW-UP][TEST] Nullabilities...
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[GitHub] spark pull request #21961: Spark 20597
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/21961#discussion_r210800762
--- Diff:
external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaSourceProvider.scala
---
@@ -231,7 +231,13 @@ private[kafka010] class KafkaSourceProvider extends
DataSourceRegister
parameters: Map[String, String],
partitionColumns: Seq[String],
outputMode: OutputMode): Sink = {
-val defaultTopic = parameters.get(TOPIC_OPTION_KEY).map(_.trim)
+// Picks the defaulttopicname from "path" key, an entry in
"parameters" Map,
+// if no topic key is present in the "parameters" Map and is provided
with key "path".
+val defaultTopic = parameters.get(TOPIC_OPTION_KEY) match {
--- End diff --
Isn't this simpler as something like
```
val defaultTopic = parameters.getOrElse(TOPIC_OPTION_KEY,
parameters.get(PATH_OPTION_KEY)).map(_.trim)
```
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[GitHub] spark issue #21537: [SPARK-24505][SQL] Convert strings in codegen to blocks:...
Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/21537 @kiszk The initial prototype or proof of concept can be in any personal branch. When we merge it to the master branch, we still need to separate it from the current codegen and make it configurable. After the release, the users can choose which one to be used. When the new IR is stable, we can then consider deprecate the current one. This is majorly for product stability. We need to follow the similar principle for any big project. @viirya @mgaido91 Let us first focus on the new IR design and prototype. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #21860: [SPARK-24901][SQL]Merge the codegen of RegularHashMap an...
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[GitHub] spark issue #21860: [SPARK-24901][SQL]Merge the codegen of RegularHashMap an...
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[GitHub] spark issue #22130: [SPARK-25137][Spark Shell] NumberFormatException` when s...
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[GitHub] spark issue #22126: [SPARK-23938][SQL][FOLLOW-UP][TEST] Nullabilities of val...
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[GitHub] spark issue #22126: [SPARK-23938][SQL][FOLLOW-UP][TEST] Nullabilities of val...
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[GitHub] spark issue #22130: [SPARK-25137][Spark Shell] NumberFormatException` when s...
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[GitHub] spark pull request #22110: [SPARK-25122][SQL] Deduplication of supports equa...
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22110#discussion_r210561778
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/TypeUtils.scala
---
@@ -73,4 +73,14 @@ object TypeUtils {
}
x.length - y.length
}
+
+ /**
+ * Returns true if elements of the data type could be used as items of a
hash set or as keys
+ * of a hash map.
+ */
+ def typeCanBeHashed(dataType: DataType): Boolean = dataType match {
--- End diff --
we should, and I believe Spark has enforced it with style checker: when you
override `equals`, you must override `hashCode` too.
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[GitHub] spark issue #22031: [SPARK-23932][SQL] Higher order function zip_with
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[GitHub] spark issue #22031: [SPARK-23932][SQL] Higher order function zip_with
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[GitHub] spark issue #22031: [SPARK-23932][SQL] Higher order function zip_with
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[GitHub] spark issue #22031: [SPARK-23932][SQL] Higher order function zip_with
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[GitHub] spark issue #22110: [SPARK-25122][SQL] Deduplication of supports equals code
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[GitHub] spark issue #22110: [SPARK-25122][SQL] Deduplication of supports equals code
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[GitHub] spark issue #22104: [SPARK-24721][SQL] Exclude Python UDFs filters in FileSo...
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[GitHub] spark issue #22031: [SPARK-23932][SQL] Higher order function zip_with
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[GitHub] spark issue #22121: [SPARK-25133][SQL][Doc]AVRO data source guide
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[GitHub] spark issue #22117: [SPARK-23654][BUILD] remove jets3t as a dependency of sp...
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