Maxim Gekk created SPARK-23649:
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Summary: CSV schema inferring fails on some UTF-8 chars
Key: SPARK-23649
URL: https://issues.apache.org/jira/browse/SPARK-23649
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.3.0
Reporter: Maxim Gekk
Schema inferring of CSV files fails if the file contains a char starts from
*0xFF.*
{code:java}
spark.read.option("header", "true").csv("utf8xFF.csv")
{code}
{code:java}
java.lang.ArrayIndexOutOfBoundsException: 63
at
org.apache.spark.unsafe.types.UTF8String.numBytesForFirstByte(UTF8String.java:191)
at org.apache.spark.unsafe.types.UTF8String.numChars(UTF8String.java:206)
{code}
Here is content of the file:
{code:java}
hexdump -C ~/tmp/utf8xFF.csv
00000000 63 68 61 6e 6e 65 6c 2c 63 6f 64 65 0d 0a 55 6e |channel,code..Un|
00000010 69 74 65 64 2c 31 32 33 0d 0a 41 42 47 55 4e ff |ited,123..ABGUN.|
00000020 2c 34 35 36 0d |,456.|
00000025
{code}
Schema inferring doesn't fail in multiline mode:
{code}
spark.read.option("header", "true").option("multiline",
"true").csv("utf8xFF.csv")
{code}
{code:java}
+-------+-----+
|channel|code
+-------+-----+
| United| 123
| ABGUN�| 456
+-------+-----+
{code}
and Spark is able to read the csv file if the schema is specified:
{code}
import org.apache.spark.sql.types._
val schema = new StructType().add("channel", StringType).add("code", StringType)
spark.read.option("header", "true").schema(schema).csv("utf8xFF.csv").show
{code}
{code:java}
+-------+----+
|channel|code|
+-------+----+
| United| 123|
| ABGUN�| 456|
+-------+----+
{code}
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