title: org.apache.spark.sql.catalyst.parser.ParseException: in spark scala cassandra api
body: <p>i have written the below spark scala code, where in i am trying to implement spark cassandra api.
  when i try to run it ,i am getting the exception like input mismatch on the date field. and automatically its populating with the data values.
  i am not able to understand to solve this.
  please help me on the same.</p>
  
  <p>Below is the method which is converting long to Date format:</p>
  
  <pre><code>def getTimeInMillis2Date( timeInMillis :Long):Date = {
          if (timeInMillis == 0l) {
              return null;
          }
          val calendar = Calendar.getInstance()
          calendar.setTimeInMillis(timeInMillis)
          val date = calendar.getTime()
          return date;
      }
  </code></pre>
  
  <hr>
  
  <p>Below is the method, which is using the Date: [edit-2]</p>
  
  <pre><code>def getCurrentTrip(s_id1: Long, a_id1: String, summ_typ1: String, summ_dt1:Date, trp_summ_Id1: String): Boolean = {
  
           var foundtrip = false
  
  
  
           val df_read2 = sparkSession.read
                               .format("org.apache.spark.sql.cassandra")
                               .option("spark.cassandra.connection.host","host")
                               .option("spark.cassandra.connection.port","9042")
                               .option( "spark.cassandra.auth.username","username")
                               .option("spark.cassandra.auth.password","pass")
                               .option("keyspace","ap")
                               .option("table","t_s_data")
                               .load()
  
  
           df_read2.createOrReplaceTempView("query_data2")
  
            var sqlDate: java.sql.Date = new java.sql.Date(summ_dt1.getTime());
  
           var res = sparkSession.sql(s"select * from ap.t_s_data where s_id =$s_id1 and a_id =$a_id1 and summ_typ =$summ_typ1 and summ_dt =$sqlDate and trp_summ_id =$trp_summ_Id1")
  
           val row = res.first()
           if (row != null) {
               println ("Found Trip")
               foundtrip = true
            } else {
                println ("Not Found")
                foundtrip = false
            }
        foundtrip
  
      }
  
      -------------------------------------------------------------------------------
      ERROR Stacktrace:
  
  
  
      18/09/20 17:29:14 ERROR app.ProcessMPacket$: error for processing this event For M-packet
  org.apache.spark.sql.AnalysisException: cannot resolve '(query_data2.`summ_dt` = ((1974 - 11) - 12))' due to data type mismatch: differing types in '(query_data2.`summ_dt` = ((1974 - 11) - 12))' (timestamp and int).; line 1 pos 130;
  'Project [*]
  +- 'Filter ((((service_id#120L = cast(1000001 as bigint)) &amp;&amp; (cast(asset_id#121 as int) = 50000000)) &amp;&amp; (summ_typ#122 = T)) &amp;&amp; ((summ_dt#123 = ((1974 - 11) - 12)) &amp;&amp; (trp_summ_id#124 = (((('8e85b4a3 - 'fbe5) - '322b) - 'aaf2) - '23f335200848))))
     +- SubqueryAlias query_data2
        +- Relation[service_id#120L,asset_id#121,summ_typ#122,summ_dt#123,trp_summ_id#124,asset_serial_no#125,avg_sp#126,c_dist#127,c_epa#128,c_gal#129,c_mil#130,device_id#131,device_serial_no#132,dist#133,en_addr#134,en_dt#135,en_lat#136,en_long#137,epa#138,gal#139,h_dist#140,h_epa#141,h_gal#142,h_mil#143,... 11 more fields] org.apache.spark.sql.cassandra.CassandraSourceRelation@38f4a1ee
  
      at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
      at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:93)
      at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:85)
      at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
      at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
      at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
      at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:288)
      at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
      at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
      at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
      at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
      at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
      at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:286)
      at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
      at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
      at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
      at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
      at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
      at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:286)
      at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:95)
      at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:95)
      at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpression$1(QueryPlan.scala:106)
      at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:116)
      at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1.apply(QueryPlan.scala:125)
      at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
      at org.apache.spark.sql.catalyst.plans.QueryPlan.mapExpressions(QueryPlan.scala:125)
      at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:95)
      at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:85)
      at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:80)
      at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
      at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:126)
      at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:126)
      at scala.collection.immutable.List.foreach(List.scala:392)
      at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:126)
      at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:80)
      at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:91)
      at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:104)
      at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:57)
      at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:55)
      at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:47)
      at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:74)
      at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:638)
      at com.vzt.afm.hum.dh.util.CassandraUtils$.getCurrentTrip(CassandraUtils.scala:253)
      at com.vzt.afm.hum.dh.app.ProcessMPacket$$anonfun$1$$anonfun$apply$1.apply(ProcessMPacket.scala:169)
      at com.vzt.afm.hum.dh.app.ProcessMPacket$$anonfun$1$$anonfun$apply$1.apply(ProcessMPacket.scala:129)
      at scala.collection.immutable.List.foreach(List.scala:392)
      at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
      at scala.collection.mutable.ListBuffer.foreach(ListBuffer.scala:45)
      at com.vzt.afm.hum.dh.app.ProcessMPacket$$anonfun$1.apply(ProcessMPacket.scala:129)
      at com.vzt.afm.hum.dh.app.ProcessMPacket$$anonfun$1.apply(ProcessMPacket.scala:75)
      at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:800)
      at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:800)
      at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
      at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
      at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
      at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
      at org.apache.spark.scheduler.Task.run(Task.scala:109)
      at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
      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)
  </code></pre>