Github user jayadevanmurali commented on the pull request:
https://github.com/apache/spark/pull/10983#issuecomment-177392588
Thanks @hvanhovell , Got your point. I updated my code and repeat the
steps. I was able to replicate this. Please check the steps
jayadevan@Satellite-L640:~/spark$ ./bin/spark-shell
NOTE: SPARK_PREPEND_CLASSES is set, placing locally compiled Spark classes
ahead of assembly.
Using Spark's default log4j profile:
org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel).
16/01/31 09:27:57 WARN NativeCodeLoader: Unable to load native-hadoop
library for your platform... using builtin-java classes where applicable
16/01/31 09:27:57 WARN Utils: Your hostname, Satellite-L640 resolves to a
loopback address: 127.0.1.1, but we couldn't find any external IP address!
16/01/31 09:27:57 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to
another address
Spark context available as sc (master = local[*], app id =
local-1454212680541).
SQL context available as sqlContext.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.0.0-SNAPSHOT
/_/
Using Scala version 2.11.7 (Java HotSpot(TM) 64-Bit Server VM, Java
1.7.0_80)
Type in expressions to have them evaluated.
Type :help for more information.
scala> import org.apache.spark.sql.types.{StringType, StructField,
StructType}
import org.apache.spark.sql.types.{StringType, StructField, StructType}
scala> import org.apache.spark.sql.{DataFrame, Row, SQLContext}
import org.apache.spark.sql.{DataFrame, Row, SQLContext}
scala> import org.apache.spark.{SparkContext, SparkConf}
import org.apache.spark.{SparkContext, SparkConf}
scala> val rows = List(Row("foo"), Row("bar"));
rows: List[org.apache.spark.sql.Row] = List([foo], [bar])
scala> val schema = StructType(Seq(StructField("col", StringType)));
schema: org.apache.spark.sql.types.StructType =
StructType(StructField(col,StringType,true))
scala> val rdd = sc.parallelize(rows);
rdd: org.apache.spark.rdd.RDD[org.apache.spark.sql.Row] =
ParallelCollectionRDD[0] at parallelize at <console>:29
scala> val df = sqlContext.createDataFrame(rdd, schema)
df: org.apache.spark.sql.DataFrame = [col: string]
scala> df.registerTempTable("t~")
scala> df.sqlContext.dropTempTable("t~")
org.apache.spark.sql.AnalysisException: NoViableAltException(327@[209:20: (
DOT id2= identifier )?])
; line 1 pos 1
at
org.apache.spark.sql.catalyst.parser.ParseErrorReporter.throwError(ParseDriver.scala:158)
at
org.apache.spark.sql.catalyst.parser.ParseErrorReporter.throwError(ParseDriver.scala:147)
at
org.apache.spark.sql.catalyst.parser.ParseDriver$.parse(ParseDriver.scala:95)
at
org.apache.spark.sql.catalyst.parser.ParseDriver$.parseTableName(ParseDriver.scala:42)
at
org.apache.spark.sql.catalyst.CatalystQl.parseTableIdentifier(CatalystQl.scala:81)
at org.apache.spark.sql.SQLContext.table(SQLContext.scala:811)
at org.apache.spark.sql.SQLContext.dropTempTable(SQLContext.scala:738)
... 49 elided
So I will close this pull request and raise a new one.
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