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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2018/01/16 13:54:00 UTC
[jira] [Commented] (SPARK-14948) Exception when joining DataFrames
derived form the same DataFrame
[ https://issues.apache.org/jira/browse/SPARK-14948?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16327139#comment-16327139 ]
Apache Spark commented on SPARK-14948:
--------------------------------------
User 'cloud-fan' has created a pull request for this issue:
https://github.com/apache/spark/pull/20276
> Exception when joining DataFrames derived form the same DataFrame
> -----------------------------------------------------------------
>
> Key: SPARK-14948
> URL: https://issues.apache.org/jira/browse/SPARK-14948
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.6.0
> Reporter: Saurabh Santhosh
> Priority: Major
>
> h2. Spark Analyser is throwing the following exception in a specific scenario :
> h2. Exception :
> org.apache.spark.sql.AnalysisException: resolved attribute(s) F1#3 missing from asd#5,F2#4,F1#6,F2#7 in operator !Project [asd#5,F1#3];
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:38)
> h2. Code :
> {code:title=SparkClient.java|borderStyle=solid}
> StructField[] fields = new StructField[2];
> fields[0] = new StructField("F1", DataTypes.StringType, true, Metadata.empty());
> fields[1] = new StructField("F2", DataTypes.StringType, true, Metadata.empty());
> JavaRDD<Row> rdd =
> sparkClient.getJavaSparkContext().parallelize(Arrays.asList(RowFactory.create("a", "b")));
> DataFrame df = sparkClient.getSparkHiveContext().createDataFrame(rdd, new StructType(fields));
> sparkClient.getSparkHiveContext().registerDataFrameAsTable(df, "t1");
> DataFrame aliasedDf = sparkClient.getSparkHiveContext().sql("select F1 as asd, F2 from t1");
> sparkClient.getSparkHiveContext().registerDataFrameAsTable(aliasedDf, "t2");
> sparkClient.getSparkHiveContext().registerDataFrameAsTable(df, "t3");
>
> DataFrame join = aliasedDf.join(df, aliasedDf.col("F2").equalTo(df.col("F2")), "inner");
> DataFrame select = join.select(aliasedDf.col("asd"), df.col("F1"));
> select.collect();
> {code}
> h2. Observations :
> * This issue is related to the Data Type of Fields of the initial Data Frame.(If the Data Type is not String, it will work.)
> * It works fine if the data frame is registered as a temporary table and an sql (select a.asd,b.F1 from t2 a inner join t3 b on a.F2=b.F2) is written.
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