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https://issues.apache.org/jira/browse/SPARK-24068?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-24068:
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Fix Version/s: 2.3.1
> 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
> Assignee: Maxim Gekk
> Priority: Major
> Fix For: 2.3.1, 2.4.0
>
>
> 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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