[geomesa-users] GEOMESA Spark SQL argument type mismatch on string field

[Dave Boyd <dboyd@xxxxxxxxxxxxxxxxx>]

All:
   I am running geomesa-accumulo-spark-runtime_2.11-2.2.2-SNAPSHOT within a zeppelin notebook.
I am having an interesting problem getting the SQL parsed whenever I try to do an equals compare on
a string field.  Maybe I am just not getting the syntax correct.
I create the dataframe as follows:

val linkagesdataFrame = spark.read.format("geomesa").options(dsParams).option("geomesa.feature", "coalescelinkage").load()
linkagesdataFrame.createOrReplaceTempView("linkageview")

The schema for the data frame is:

root |-- __fid__: string (nullable = false) |-- entity2version: string (nullable = true) |-- linklabel: string (nullable = true) |-- linktype: integer (nullable = true) |-- source: string (nullable = true) |-- datecreated: timestamp (nullable = true) |-- title: string (nullable = true) |-- version: string (nullable = true) |-- entity2name: string (nullable = true) |-- entity2source: string (nullable = true) |-- objectkey: string (nullable = true) |-- lastmodified: timestamp (nullable = true) |-- name: string (nullable = true) |-- entity2key: string (nullable = true) |-- linkstatus: integer (nullable = true)

This SQL statement fails to parse with the below error:

%sql
select * from linkageview where name = "NGrams"

java.lang.IllegalArgumentException: argument type mismatch at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at org.locationtech.geomesa.spark.SparkVersions$$anonfun$1$$anonfun$apply$2.apply(SparkVersions.scala:34) at org.locationtech.geomesa.spark.SparkVersions$$anonfun$1$$anonfun$apply$2.apply(SparkVersions.scala:34) at org.locationtech.geomesa.spark.SparkVersions$.copy(SparkVersions.scala:48) at org.apache.spark.sql.SQLRules$SpatialOptimizationsRule$$anonfun$apply$1.applyOrElse(SQLRules.scala:261) at org.apache.spark.sql.SQLRules$SpatialOptimizationsRule$$anonfun$apply$1.applyOrElse(SQLRules.scala:221) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:288) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:288) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:287) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188) at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188) at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:277) at org.apache.spark.sql.SQLRules$SpatialOptimizationsRule$.apply(SQLRules.scala:221) at org.apache.spark.sql.SQLRules$SpatialOptimizationsRule$.apply(SQLRules.scala:143) 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$1.apply(RuleExecutor.scala:74) at scala.collection.immutable.List.foreach(List.scala:381) at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74) at org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:73) at org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:73) at org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:79) at org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:75) at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:84) at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:84) at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2791) at org.apache.spark.sql.Dataset.head(Dataset.scala:2112) at org.apache.spark.sql.Dataset.take(Dataset.scala:2327) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at org.apache.zeppelin.spark.SparkZeppelinContext.showData(SparkZeppelinContext.java:108) at org.apache.zeppelin.spark.SparkSqlInterpreter.interpret(SparkSqlInterpreter.java:135) at org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:103) at org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:632) at org.apache.zeppelin.scheduler.Job.run(Job.java:188) at org.apache.zeppelin.scheduler.ParallelScheduler$JobRunner.run(ParallelScheduler.java:162) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)

Interestingly the query:

select * from linkageview where name like 'NGrams%'

Works just fine.

This only seems to affect direct equal comparisons of string fields.
I have run a number of other complex queries with aggregations and
even some gnarly joins that work just fine.

Any thoughts?

-- 
========= mailto:dboyd@xxxxxxxxxxxxxxxxx ============
David W. Boyd                     
VP,  Data Solutions       
10432 Balls Ford, Suite 240  
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ISO/IEC JTC1 WG9, editor ISO/IEC 20547 Big Data Reference Architecture
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