[jira] [Commented] (SPARK-42193) dataframe API filter criteria throwing ParseException when reading a JDBC column name with special characters

["Max Gekk (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-42193?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17687756#comment-17687756 ] 

Max Gekk commented on SPARK-42193:
----------------------------------

I haven't reproduced the issue on the recent master. Seems like it has been already fixed by [~huaxingao] in https://issues.apache.org/jira/browse/SPARK-41990 also cc [~dongjoon]

> dataframe API filter criteria throwing ParseException when reading a JDBC column name with special characters
> -------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-42193
>                 URL: https://issues.apache.org/jira/browse/SPARK-42193
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 3.3.0
>            Reporter: Shanmugavel Kuttiyandi Chandrakasu
>            Priority: Minor
>
> *On Spark 3.3.0,* when reading from a JDBC table(used SQLite to repro) using spark.read.jdbc command with sqlite-jdbc:3.34.0.jar on a table and column name containing special characters. Dataframe API filter criteria fails with parse Exception 
> *[#Script:]*
> {code:java}
> from pyspark.sql import SparkSession
> spark = SparkSession \
>     .builder \
>     .appName("Databricks Support") \
>     .config("spark.jars.packages", "org.xerial:sqlite-jdbc:3.34.0") \
>     .getOrCreate()
> columns = ["id", "/abc/column", "value"]
> data = [(1, 'A', 100), (2, 'B', 200), (3, 'B', 300)]
> rdd = spark.sparkContext.parallelize(data)
> df = spark.createDataFrame(rdd).toDF(*columns)
> options = {"url": "jdbc:sqlite:/<local-path>/spark-3.3.1-bin-hadoop3/jars/test.db", "dbtable": '"/abc/table"', "driver": "org.sqlite.JDBC"}
> df.coalesce(1).write.format("jdbc").options(**options).mode("append").save()
> df_1 = spark.read.format("jdbc") \
>     .option("url", "jdbc:sqlite:/<local-path>/spark-3.3.1-bin-hadoop3/jars/test.db") \
>     .option("dbtable", '"/abc/table"') \
>     .option("driver", "org.sqlite.JDBC") \
>     .load()
> df_2 = df_1.filter("`/abc/column` = 'B'")
> df_2.show() {code}
> Error:
> {code:java}
> ``` Traceback (most recent call last):
>  File "<stdin>", line 1, in <module>
>  File "/opt/homebrew/Cellar/apache-spark/3.3.1/libexec/python/pyspark/sql/dataframe.py", line 606, in show
>   print(self._jdf.showString(n, 20, vertical))
>  File "/opt/homebrew/Cellar/apache-spark/3.3.1/libexec/python/lib/py4j-0.10.9.5-src.zip/py4j/java_gateway.py", line 1321, in __call__
>  File "/opt/homebrew/Cellar/apache-spark/3.3.1/libexec/python/pyspark/sql/utils.py", line 196, in deco
>   raise converted from None
> pyspark.sql.utils.ParseException: 
> Syntax error at or near '/': extra input '/'(line 1, pos 0)
> == SQL ==
> /abc/column
> ^^^```  {code}
> However, when using Spark 3.2.1, we are able to successfully apply dataframe.filter option
> {code:java}
> >>> df_2.show()
> +---+-----------+-----+
> | id|/abc/column|value|
> +---+-----------+-----+
> |  2|          B|  200|
> |  3|          B|  300|
> +---+-----------+-----+ {code}
> *Repro steps:*
>  # Download [Spark 3.2.1 in local |https://archive.apache.org/dist/spark/spark-3.2.1/spark-3.2.1-bin-hadoop3.2.tgz]
>  # Download and Copy the sqlite-jdbc:3.34.0.jar into the jar folder present in the local spark download folder
>  # Run the above [#script] by providing the jar path 
>  # This will create a */abc/table* with column */abc/column*  and returns result when applying filter criteria
>  # Download spark ** [3.3.0 in local|https://www.apache.org/dyn/closer.lua/spark/spark-3.3.1/spark-3.3.1-bin-hadoop3.tgz]
>  # Repeat #2, #3 
>  # Fails with parse exception. 
> could you please let us know how we can filter on the special characters column or escape them on spark version 3.3.0?



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