Hey there,
1.) I'm loading 2 avro files with that have slightly different schema
df1 = sqlc.load(file1, "com.databricks.spark.avro")
df2 = sqlc.load(file2, "com.databricks.spark.avro")
2.) I want to unionAll them
nfd = dfs1.unionAll(dfs2)
3.) Getting the following error
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-190-a86d9adbea83> in <module>()
17
18
---> 19 nfd = dfs1.unionAll(dfs2)
20
21
/home/hadoop/spark/python/pyspark/sql/dataframe.pyc in unionAll(self, other)
669 This is equivalent to `UNION ALL` in SQL.
670 """
--> 671 return DataFrame(self._jdf.unionAll(other._jdf),
self.sql_ctx)
672
673 def intersect(self, other):
/home/hadoop/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
__call__(self, *args)
536 answer = self.gateway_client.send_command(command)
537 return_value = get_return_value(answer, self.gateway_client,
--> 538 self.target_id, self.name)
539
540 for temp_arg in temp_args:
/home/hadoop/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py in
get_return_value(answer, gateway_client, target_id, name)
298 raise Py4JJavaError(
299 'An error occurred while calling {0}{1}{2}.\n'.
--> 300 format(target_id, '.', name), value)
301 else:
302 raise Py4JError(
Py4JJavaError: An error occurred while calling o76196.unionAll.
: org.apache.spark.sql.AnalysisException: unresolved operator 'Union ;
at
org.apache.spark.sql.catalyst.analysis.CheckAnalysis.failAnalysis(CheckAnalysis.scala:37)
at
org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$apply$3.apply(CheckAnalysis.scala:97)
at
org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$apply$3.apply(CheckAnalysis.scala:43)
at
org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:88)
at
org.apache.spark.sql.catalyst.analysis.CheckAnalysis.apply(CheckAnalysis.scala:43)
at
org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:1069)
at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:133)
at
org.apache.spark.sql.DataFrame.logicalPlanToDataFrame(DataFrame.scala:157)
at org.apache.spark.sql.DataFrame.unionAll(DataFrame.scala:641)
at sun.reflect.GeneratedMethodAccessor36.invoke(Unknown Source)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
at py4j.Gateway.invoke(Gateway.java:259)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:207)
at java.lang.Thread.run(Thread.java:745)
---------------------------------------------------------------------------
4.) Is it possible to automatically merge 2 DFs with different schemas like
that? Am I doing sth. wrong?
Much appreciated!
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