You know, I actually have one of the columns called "timestamp" ! This may really cause the problem reported in the bug you linked, I guess.
On Wed, Mar 18, 2015 at 3:37 PM, Cheng Lian <lian.cs....@gmail.com> wrote: > I suspect that you hit this bug > https://issues.apache.org/jira/browse/SPARK-6250, it depends on the > actual contents of your query. > > Yin had opened a PR for this, although not merged yet, it should be a > valid fix https://github.com/apache/spark/pull/5078 > > This fix will be included in 1.3.1. > > Cheng > > On 3/18/15 10:04 PM, Roberto Coluccio wrote: > > Hi Cheng, thanks for your reply. > > The query is something like: > > SELECT * FROM ( >> SELECT m.column1, IF (d.columnA IS NOT null, d.columnA, m.column2), >> ..., m.columnN FROM tableD d RIGHT OUTER JOIN tableM m on m.column2 = >> d.columnA WHERE m.column2!=\"None\" AND d.columnA!=\"\" >> UNION ALL >> SELECT ... [another SELECT statement with different conditions but same >> tables] >> UNION ALL >> SELECT ... [another SELECT statement with different conditions but same >> tables] >> ) a > > > I'm using just sqlContext, no hiveContext. Please, note once again that > this perfectly worked w/ Spark 1.1.x. > > The tables, i.e. tableD and tableM are previously registered with the > RDD.registerTempTable method, where the input RDDs are actually a > RDD[MyCaseClassM/D], with MyCaseClassM and MyCaseClassD being simple case > classes with only (and less than 22) String fields. > > Hope the situation is a bit more clear. Thanks anyone who will help me > out here. > > Roberto > > > > On Wed, Mar 18, 2015 at 12:09 PM, Cheng Lian <lian.cs....@gmail.com> > wrote: > >> Would you mind to provide the query? If it's confidential, could you >> please help constructing a query that reproduces this issue? >> >> Cheng >> >> On 3/18/15 6:03 PM, Roberto Coluccio wrote: >> >> Hi everybody, >> >> When trying to upgrade from Spark 1.1.1 to Spark 1.2.x (tried both >> 1.2.0 and 1.2.1) I encounter a weird error never occurred before about >> which I'd kindly ask for any possible help. >> >> In particular, all my Spark SQL queries fail with the following >> exception: >> >> java.lang.RuntimeException: [1.218] failure: identifier expected >>> >>> [my query listed] >>> ^ >>> at scala.sys.package$.error(package.scala:27) >>> at >>> org.apache.spark.sql.catalyst.AbstractSparkSQLParser.apply(SparkSQLParser.scala:33) >>> at >>> org.apache.spark.sql.SQLContext$$anonfun$1.apply(SQLContext.scala:79) >>> at >>> org.apache.spark.sql.SQLContext$$anonfun$1.apply(SQLContext.scala:79) >>> at >>> org.apache.spark.sql.catalyst.SparkSQLParser$$anonfun$org$apache$spark$sql$catalyst$SparkSQLParser$$others$1.apply(SparkSQLParser.scala:174) >>> at >>> org.apache.spark.sql.catalyst.SparkSQLParser$$anonfun$org$apache$spark$sql$catalyst$SparkSQLParser$$others$1.apply(SparkSQLParser.scala:173) >>> at scala.util.parsing.combinator.Parsers$Success.map(Parsers.scala:136) >>> at scala.util.parsing.combinator.Parsers$Success.map(Parsers.scala:135) >>> at >>> scala.util.parsing.combinator.Parsers$Parser$$anonfun$map$1.apply(Parsers.scala:242) >>> at >>> scala.util.parsing.combinator.Parsers$Parser$$anonfun$map$1.apply(Parsers.scala:242) >>> ... >> >> >> >> The unit tests I've got for testing this stuff fail both if I >> build+test the project with Maven and if I run then as single ScalaTest >> files or test suites/packages. >> >> When running my app as usual on EMR in YARN-cluster mode, I get the >> following: >> >> 15/03/17 11:32:14 INFO yarn.ApplicationMaster: Final app status: FAILED, >> exitCode: 15, (reason: User class threw exception: [1.218] failure: >> identifier expected >> >> SELECT * FROM ... (my query) >> >> >> ^) >> Exception in thread "Driver" java.lang.RuntimeException: [1.218] failure: >> identifier expected >> >> SELECT * FROM ... (my query) >> >> >> ^ >> at scala.sys.package$.error(package.scala:27) >> at >> org.apache.spark.sql.catalyst.AbstractSparkSQLParser.apply(SparkSQLParser.scala:33) >> at org.apache.spark.sql.SQLContext$$anonfun$1.apply(SQLContext.scala:79) >> at org.apache.spark.sql.SQLContext$$anonfun$1.apply(SQLContext.scala:79) >> at >> org.apache.spark.sql.catalyst.SparkSQLParser$$anonfun$org$apache$spark$sql$catalyst$SparkSQLParser$$others$1.apply(SparkSQLParser.scala:174) >> at >> org.apache.spark.sql.catalyst.SparkSQLParser$$anonfun$org$apache$spark$sql$catalyst$SparkSQLParser$$others$1.apply(SparkSQLParser.scala:173) >> at scala.util.parsing.combinator.Parsers$Success.map(Parsers.scala:136) >> at scala.util.parsing.combinator.Parsers$Success.map(Parsers.scala:135) >> at >> scala.util.parsing.combinator.Parsers$Parser$$anonfun$map$1.apply(Parsers.scala:242) >> at >> scala.util.parsing.combinator.Parsers$Parser$$anonfun$map$1.apply(Parsers.scala:242) >> at scala.util.parsing.combinator.Parsers$$anon$3.apply(Parsers.scala:222) >> at >> scala.util.parsing.combinator.Parsers$Parser$$anonfun$append$1$$anonfun$apply$2.apply(Parsers.scala:254) >> at >> scala.util.parsing.combinator.Parsers$Parser$$anonfun$append$1$$anonfun$apply$2.apply(Parsers.scala:254) >> at >> scala.util.parsing.combinator.Parsers$Failure.append(Parsers.scala:202) >> at >> scala.util.parsing.combinator.Parsers$Parser$$anonfun$append$1.apply(Parsers.scala:254) >> at >> scala.util.parsing.combinator.Parsers$Parser$$anonfun$append$1.apply(Parsers.scala:254) >> at scala.util.parsing.combinator.Parsers$$anon$3.apply(Parsers.scala:222) >> at >> scala.util.parsing.combinator.Parsers$$anon$2$$anonfun$apply$14.apply(Parsers.scala:891) >> at >> scala.util.parsing.combinator.Parsers$$anon$2$$anonfun$apply$14.apply(Parsers.scala:891) >> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) >> at scala.util.parsing.combinator.Parsers$$anon$2.apply(Parsers.scala:890) >> at >> scala.util.parsing.combinator.PackratParsers$$anon$1.apply(PackratParsers.scala:110) >> at >> org.apache.spark.sql.catalyst.AbstractSparkSQLParser.apply(SparkSQLParser.scala:31) >> at >> org.apache.spark.sql.SQLContext$$anonfun$parseSql$1.apply(SQLContext.scala:83) >> at >> org.apache.spark.sql.SQLContext$$anonfun$parseSql$1.apply(SQLContext.scala:83) >> at scala.Option.getOrElse(Option.scala:120) >> at org.apache.spark.sql.SQLContext.parseSql(SQLContext.scala:83) >> at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:303) >> at mycompany.mypackage.MyClassFunction.apply(MyClassFunction.scala:34) >> at mycompany.mypackage.MyClass$.main(MyClass.scala:254) at >> mycompany.mypackage.MyClass.main(MyClass.scala) at >> sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >> at >> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) >> at >> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >> at java.lang.reflect.Method.invoke(Method.java:606) >> at >> org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:441) >> 15/03/17 11:32:14 INFO yarn.ApplicationMaster: Invoking sc stop from >> shutdown hook >> >> Any suggestions? >> >> Thanks, >> >> Roberto >> >> >> > >
