[jira] [Created] (SPARK-24068) CSV schema inferring doesn't work for compressed files

[Maxim Gekk (JIRA)]

Maxim Gekk created SPARK-24068:
----------------------------------

             Summary: 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


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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