[
https://issues.apache.org/jira/browse/SPARK-21215?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16065329#comment-16065329
]
Michael Kunkel commented on SPARK-21215:
----------------------------------------
The "resolution for this by [~sowen] was to put this on the spark mailing list.
But I am sure this is just a scam to toss questions because the mailing list is
no longer accepting emails.
When sending a email to the mailing list, a reply is given
Hello,
This employee can no longer access email on this account. Your email will not
be forwarded.
So, this is not resolved.
> Exception in thread "main" org.apache.spark.sql.AnalysisException: cannot
> resolve
> ---------------------------------------------------------------------------------
>
> Key: SPARK-21215
> URL: https://issues.apache.org/jira/browse/SPARK-21215
> Project: Spark
> Issue Type: Bug
> Components: Java API, SQL
> Affects Versions: 2.1.1
> Environment: macOSX
> Reporter: Michael Kunkel
>
> First Spark project.
> I have a Java method that returns a Dataset<Row>. I want to convert this to a
> Dataset<Object>, where the Object is named StatusChangeDB. I have created a
> POJO StatusChangeDB.java and coded it with all the query objects found in the
> mySQL table.
> I then create a Encoder and convert the Dataset<Row> to a
> Dataset<StatusChangeDB>. However when I try to .show() the values of the
> Dataset<StatusChangeDB> I receive the error
> bq.
> bq. Exception in thread "main" org.apache.spark.sql.AnalysisException: cannot
> resolve '`hvpinid_quad`' given input columns: [status_change_type,
> superLayer, loclayer, sector, locwire];
> bq. at
> org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
> bq. at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:86)
> bq. at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:83)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:290)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:290)
> bq. at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:289)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:287)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:287)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:305)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:287)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:287)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:287)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4$$anonfun$apply$10.apply(TreeNode.scala:324)
> bq. at
> scala.collection.MapLike$MappedValues$$anonfun$iterator$3.apply(MapLike.scala:246)
> bq. at
> scala.collection.MapLike$MappedValues$$anonfun$iterator$3.apply(MapLike.scala:246)
> bq. at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> bq. at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> bq. at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> bq. at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
> bq. at scala.collection.IterableLike$$anon$1.foreach(IterableLike.scala:311)
> bq. at
> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
> bq. at
> scala.collection.mutable.MapBuilder.$plus$plus$eq(MapBuilder.scala:25)
> bq. at
> scala.collection.TraversableViewLike$class.force(TraversableViewLike.scala:88)
> bq. at scala.collection.IterableLike$$anon$1.force(IterableLike.scala:311)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:332)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:305)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:287)
> bq. at
> org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:255)
> bq. at
> org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:255)
> bq. at
> org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpression$1(QueryPlan.scala:266)
> bq. at
> org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:276)
> bq. at
> org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$6.apply(QueryPlan.scala:285)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
> bq. at
> org.apache.spark.sql.catalyst.plans.QueryPlan.mapExpressions(QueryPlan.scala:285)
> bq. at
> org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:255)
> bq. at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:83)
> bq. at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:76)
> bq. at
> org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:128)
> bq. at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:76)
> bq. at
> org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:57)
> bq. at
> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.resolveAndBind(ExpressionEncoder.scala:259)
> bq. at org.apache.spark.sql.Dataset.<init>(Dataset.scala:209)
> bq. at org.apache.spark.sql.Dataset.<init>(Dataset.scala:167)
> bq. at org.apache.spark.sql.Dataset$.apply(Dataset.scala:58)
> bq. at org.apache.spark.sql.Dataset.as(Dataset.scala:376)
> I do not know how to have whomever replicate this, but here are some methods
> that are used on my end. I hope the error can be seen from the following
> codes:
> public static Dataset<Row> mySqlDataset() {
> SparkSession spSession = getSession();
> spSession.sql("set spark.sql.caseSensitive=false");
> Dataset<Row> demoDf =
> spSession.read().format("jdbc").options(jdbcOptions()).load();
> }
> where jdbcOptions() are
> public static Map<String, String> jdbcOptions() {
> Map<String, String> jdbcOptions = new HashMap<String, String>();
> jdbcOptions.put("url", "jdbc:mysql://localhost:3306/test");
> jdbcOptions.put("driver", "com.mysql.jdbc.Driver");
> jdbcOptions.put("dbtable", "status_change");
> jdbcOptions.put("user", "root");
> jdbcOptions.put("password", "");
> return jdbcOptions;
> }
> the method that fails is
> public Dataset<StatusChangeDB> compareRunII(String str) {
> Dataset<Row> tempDF = SparkManager.mySqlDataset()
> .select("loclayer", "superLayer", "sector",
> "locwire", "status_change_type")
> .filter(col("runno").equalTo(str));
> return tempDF.as(SparkManager.statusChangeDBEncoder());
> }
> where SparkManager.statusChangeDBEncoder() is
> public static Encoder<StatusChangeDB> statusChangeDBEncoder() {
> return Encoders.bean(StatusChangeDB.class);
> }
> and StatusChangeDB is just a POJO that works because I am able to create
> Dataset<StatusChangeDB> from a datafile.
> There is no help on Google or this forum for this error.
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
