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  1. Spark
  2. SPARK-21392

Unable to infer schema when loading large Parquet file

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    Details

    • Type: Bug
    • Status: Resolved
    • Priority: Major
    • Resolution: Invalid
    • Affects Version/s: 2.1.1, 2.2.0
    • Fix Version/s: None
    • Component/s: PySpark
    • Labels:
    • Environment:

      Spark 2.1.1. python 2.7.6

      Description

      The following boring code works up until when I read in the parquet file.

      import numpy as np
      import pandas as pd
      import pyspark
      from pyspark import SQLContext, SparkContext, SparkConf
      
      print pyspark.__version__
      sc = SparkContext(conf=SparkConf().setMaster('local'))
      df = pd.DataFrame({"mi":np.arange(100), "eid":np.arange(100)})
      print df
      sqlc = SQLContext(sc)
      df = sqlc.createDataFrame(df)
      df = df.createOrReplaceTempView("outcomes")
      rdd = sqlc.sql("SELECT eid,mi FROM outcomes limit 5")
      print rdd.schema
      rdd.show()
      rdd.write.parquet("mi", mode="overwrite")
      rdd2 = sqlc.read.parquet("mi")  # FAIL!
      
      # print pyspark.__version__
      2.2.0
      
      # print df
          eid  mi
      0     0   0
      1     1   1
      2     2   2
      3     3   3
      ...
      
      [100 rows x 2 columns]
      
      # print rdd.schema
      StructType(List(StructField(eid,LongType,true),StructField(mi,LongType,true)))
      
      # rdd.show()
      +---+---+
      |eid| mi|
      +---+---+
      |  0|  0|
      |  1|  1|
      |  2|  2|
      |  3|  3|
      |  4|  4|
      +---+---+
      

      fails with:

          rdd2 = sqlc.read.parquet("mixx")
        File "/usr/local/lib/python2.7/dist-packages/pyspark/sql/readwriter.py", line 291, in parquet
          return self._df(self._jreader.parquet(_to_seq(self._spark._sc, paths)))
        File "/usr/local/lib/python2.7/dist-packages/py4j/java_gateway.py", line 1133, in __call__
          answer, self.gateway_client, self.target_id, self.name)
        File "/usr/local/lib/python2.7/dist-packages/pyspark/sql/utils.py", line 69, in deco
          raise AnalysisException(s.split(': ', 1)[1], stackTrace)
      pyspark.sql.utils.AnalysisException: u'Unable to infer schema for Parquet. It must be specified manually.;'
      

      The documentation for parquet says the format is self describing, and the full schema was available when the parquet file was saved. What gives?

      Works with master='local', but fails with my cluster is specified.

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            • Assignee:
              Unassigned
              Reporter:
              stuartreynolds Stuart Reynolds
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              • Created:
                Updated:
                Resolved: