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Posted to issues@spark.apache.org by "Michael Armbrust (JIRA)" <ji...@apache.org> on 2018/02/16 21:59:00 UTC

[jira] [Commented] (SPARK-23337) withWatermark raises an exception on struct objects

    [ https://issues.apache.org/jira/browse/SPARK-23337?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16367933#comment-16367933 ] 

Michael Armbrust commented on SPARK-23337:
------------------------------------------

This is essentially the same issue as SPARK-18084. We are taking a column name here, not an expression.  As such you can only reference top level columns.  I agree this is an annoying aspect of the API, but changing it might have to happen at a major release since it would be change in behavior.

> withWatermark raises an exception on struct objects
> ---------------------------------------------------
>
>                 Key: SPARK-23337
>                 URL: https://issues.apache.org/jira/browse/SPARK-23337
>             Project: Spark
>          Issue Type: Bug
>          Components: Structured Streaming
>    Affects Versions: 2.2.1
>         Environment: Linux Ubuntu, Spark on standalone mode
>            Reporter: Aydin Kocas
>            Priority: Major
>
> Hi,
>  
> when using a nested object (I mean an object within a struct, here concrete: _source.createTime) from a json file as the parameter for the withWatermark-method, I get an exception (see below).
> Anything else works flawlessly with the nested object.
>  
> +*{color:#14892c}works:{color}*+ 
> {code:java}
> Dataset<Row> jsonRow = spark.readStream().schema(getJSONSchema()).json(file).dropDuplicates("_id").withWatermark("myTime", "10 seconds").toDF();{code}
>  
> json structure:
> {code:java}
> root
>  |-- _id: string (nullable = true)
>  |-- _index: string (nullable = true)
>  |-- _score: long (nullable = true)
>  |-- myTime: timestamp (nullable = true)
> ..{code}
> +*{color:#d04437}does not work - nested json{color}:*+
> {code:java}
> Dataset<Row> jsonRow = spark.readStream().schema(getJSONSchema()).json(file).dropDuplicates("_id").withWatermark("_source.createTime", "10 seconds").toDF();{code}
>  
> json structure:
>  
> {code:java}
> root
>  |-- _id: string (nullable = true)
>  |-- _index: string (nullable = true)
>  |-- _score: long (nullable = true)
>  |-- _source: struct (nullable = true)
>  | |-- createTime: timestamp (nullable = true)
> ..
>  
> Exception in thread "main" org.apache.spark.sql.catalyst.errors.package$TreeNodeException: makeCopy, tree:
> 'EventTimeWatermark '_source.createTime, interval 10 seconds
> +- Deduplicate [_id#0], true
>  +- StreamingRelation DataSource(org.apache.spark.sql.SparkSession@5dbbb292,json,List(),Some(StructType(StructField(_id,StringType,true), StructField(_index,StringType,true), StructField(_score,LongType,true), StructField(_source,StructType(StructField(additionalData,StringType,true), StructField(client,StringType,true), StructField(clientDomain,BooleanType,true), StructField(clientVersion,StringType,true), StructField(country,StringType,true), StructField(countryName,StringType,true), StructField(createTime,TimestampType,true), StructField(externalIP,StringType,true), StructField(hostname,StringType,true), StructField(internalIP,StringType,true), StructField(location,StringType,true), StructField(locationDestination,StringType,true), StructField(login,StringType,true), StructField(originalRequestString,StringType,true), StructField(password,StringType,true), StructField(peerIdent,StringType,true), StructField(peerType,StringType,true), StructField(recievedTime,TimestampType,true), StructField(sessionEnd,StringType,true), StructField(sessionStart,StringType,true), StructField(sourceEntryAS,StringType,true), StructField(sourceEntryIp,StringType,true), StructField(sourceEntryPort,StringType,true), StructField(targetCountry,StringType,true), StructField(targetCountryName,StringType,true), StructField(targetEntryAS,StringType,true), StructField(targetEntryIp,StringType,true), StructField(targetEntryPort,StringType,true), StructField(targetport,StringType,true), StructField(username,StringType,true), StructField(vulnid,StringType,true)),true), StructField(_type,StringType,true))),List(),None,Map(path -> ./input/),None), FileSource[./input/], [_id#0, _index#1, _score#2L, _source#3, _type#4]
> at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
>  at org.apache.spark.sql.catalyst.trees.TreeNode.makeCopy(TreeNode.scala:385)
>  at org.apache.spark.sql.catalyst.plans.QueryPlan.mapExpressions(QueryPlan.scala:300)
>  at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:268)
>  at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$9.applyOrElse(Analyzer.scala:854)
>  at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$9.applyOrElse(Analyzer.scala:796)
>  at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:62)
>  at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:62)
>  at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
>  at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:61)
>  at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:796)
>  at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:674)
>  at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
>  at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
>  at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
>  at scala.collection.immutable.List.foldLeft(List.scala:84)
>  at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
>  at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
>  at scala.collection.immutable.List.foreach(List.scala:381)
>  at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
>  at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:69)
>  at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:67)
>  at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:50)
>  at org.apache.spark.sql.Dataset.<init>(Dataset.scala:165)
>  at org.apache.spark.sql.Dataset.<init>(Dataset.scala:171)
>  at org.apache.spark.sql.Dataset$.apply(Dataset.scala:62)
>  at org.apache.spark.sql.Dataset.withTypedPlan(Dataset.scala:2889)
>  at org.apache.spark.sql.Dataset.withWatermark(Dataset.scala:569)
>  at my.package.hpstatistics.Importer.importViaSparkStreaming(Importer.java:278)
>  at my.package.hpstatistics.Main.main(Main.java:80)
> Caused by: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: 
> Failed to copy node.
> Is otherCopyArgs specified correctly for EventTimeWatermark.
> Exception message: argument type mismatch
> ctor: public org.apache.spark.sql.catalyst.plans.logical.EventTimeWatermark(org.apache.spark.sql.catalyst.expressions.Attribute,org.apache.spark.unsafe.types.CalendarInterval,org.apache.spark.sql.catalyst.plans.logical.LogicalPlan)?
> types: class org.apache.spark.sql.catalyst.expressions.Alias, class org.apache.spark.unsafe.types.CalendarInterval, class org.apache.spark.sql.catalyst.plans.logical.Deduplicate
> args: _source#3.createTime AS createTime#12, interval 10 seconds, Deduplicate [_id#0], true
> +- StreamingRelation DataSource(org.apache.spark.sql.SparkSession@5dbbb292,json,List(),Some(StructType(StructField(_id,StringType,true), StructField(_index,StringType,true), StructField(_score,LongType,true), StructField(_source,StructType(StructField(additionalData,StringType,true), StructField(client,StringType,true), StructField(clientDomain,BooleanType,true), StructField(clientVersion,StringType,true), StructField(country,StringType,true), StructField(countryName,StringType,true), StructField(createTime,TimestampType,true), StructField(externalIP,StringType,true), StructField(hostname,StringType,true), StructField(internalIP,StringType,true), StructField(location,StringType,true), StructField(locationDestination,StringType,true), StructField(login,StringType,true), StructField(originalRequestString,StringType,true), StructField(password,StringType,true), StructField(peerIdent,StringType,true), StructField(peerType,StringType,true), StructField(recievedTime,TimestampType,true), StructField(sessionEnd,StringType,true), StructField(sessionStart,StringType,true), StructField(sourceEntryAS,StringType,true), StructField(sourceEntryIp,StringType,true), StructField(sourceEntryPort,StringType,true), StructField(targetCountry,StringType,true), StructField(targetCountryName,StringType,true), StructField(targetEntryAS,StringType,true), StructField(targetEntryIp,StringType,true), StructField(targetEntryPort,StringType,true), StructField(targetport,StringType,true), StructField(username,StringType,true), StructField(vulnid,StringType,true)),true), StructField(_type,StringType,true))),List(),None,Map(path -> ./input/),None), FileSource[./input/], [_id#0, _index#1, _score#2L, _source#3, _type#4]
> , tree:
> 'EventTimeWatermark '_source.createTime, interval 10 seconds
> +- Deduplicate [_id#0], true
>  +- StreamingRelation DataSource(org.apache.spark.sql.SparkSession@5dbbb292,json,List(),Some(StructType(StructField(_id,StringType,true), StructField(_index,StringType,true), StructField(_score,LongType,true), StructField(_source,StructType(StructField(additionalData,StringType,true), StructField(client,StringType,true), StructField(clientDomain,BooleanType,true), StructField(clientVersion,StringType,true), StructField(country,StringType,true), StructField(countryName,StringType,true), StructField(createTime,TimestampType,true), StructField(externalIP,StringType,true), StructField(hostname,StringType,true), StructField(internalIP,StringType,true), StructField(location,StringType,true), StructField(locationDestination,StringType,true), StructField(login,StringType,true), StructField(originalRequestString,StringType,true), StructField(password,StringType,true), StructField(peerIdent,StringType,true), StructField(peerType,StringType,true), StructField(recievedTime,TimestampType,true), StructField(sessionEnd,StringType,true), StructField(sessionStart,StringType,true), StructField(sourceEntryAS,StringType,true), StructField(sourceEntryIp,StringType,true), StructField(sourceEntryPort,StringType,true), StructField(targetCountry,StringType,true), StructField(targetCountryName,StringType,true), StructField(targetEntryAS,StringType,true), StructField(targetEntryIp,StringType,true), StructField(targetEntryPort,StringType,true), StructField(targetport,StringType,true), StructField(username,StringType,true), StructField(vulnid,StringType,true)),true), StructField(_type,StringType,true))),List(),None,Map(path -> ./input/),None), FileSource[./input/], [_id#0, _index#1, _score#2L, _source#3, _type#4]
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$makeCopy$1.apply(TreeNode.scala:415)
>  at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$makeCopy$1.apply(TreeNode.scala:385)
>  at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
>  ... 29 more
> {code}
>  



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