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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-24068) CSV schema inferring doesn't work for compressed files
Date Fri, 27 Apr 2018 15:56:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-24068?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16456654#comment-16456654
] 

Apache Spark commented on SPARK-24068:
--------------------------------------

User 'MaxGekk' has created a pull request for this issue:
https://github.com/apache/spark/pull/21182

> CSV schema inferring doesn't work for compressed files
> ------------------------------------------------------
>
>                 Key: SPARK-24068
>                 URL: https://issues.apache.org/jira/browse/SPARK-24068
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.3.0
>            Reporter: Maxim Gekk
>            Priority: Major
>
> Here is a simple csv file compressed by lzo
> {code}
> $ cat ./test.csv
> col1,col2
> a,1
> $ lzop ./test.csv
> $ ls
> test.csv     test.csv.lzo
> {code}
> Reading test.csv.lzo with LZO codec (see https://github.com/twitter/hadoop-lzo, for example):
> {code:scala}
> scala> val ds = spark.read.option("header", true).option("inferSchema", true).option("io.compression.codecs",
"com.hadoop.compression.lzo.LzopCodec").csv("/Users/maximgekk/tmp/issue/test.csv.lzo")
> ds: org.apache.spark.sql.DataFrame = [�LZO?: string]
> scala> ds.printSchema
> root
>  |-- �LZO: string (nullable = true)
> scala> ds.show
> +-----+
> |�LZO|
> +-----+
> |    a|
> +-----+
> {code}
> but the file can be read if the schema is specified:
> {code}
> scala> import org.apache.spark.sql.types._
> scala> val schema = new StructType().add("col1", StringType).add("col2", IntegerType)
> scala> val ds = spark.read.schema(schema).option("header", true).option("io.compression.codecs",
"com.hadoop.compression.lzo.LzopCodec").csv("test.csv.lzo")
> scala> ds.show
> +----+----+
> |col1|col2|
> +----+----+
> |   a|   1|
> +----+----+
> {code}
> Just in case, schema inferring works for the original uncompressed file:
> {code:scala}
> scala> spark.read.option("header", true).option("inferSchema", true).csv("test.csv").printSchema
> root
>  |-- col1: string (nullable = true)
>  |-- col2: integer (nullable = true)
> {code}



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