[ https://issues.apache.org/jira/browse/SPARK-44638?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
ASF GitHub Bot reassigned SPARK-44638: -------------------------------------- Assignee: (was: Apache Spark) > Unable to read from JDBC data sources when using custom schema containing > varchar > --------------------------------------------------------------------------------- > > Key: SPARK-44638 > URL: https://issues.apache.org/jira/browse/SPARK-44638 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 3.1.0, 3.2.4, 3.3.2, 3.4.1 > Reporter: Michael Said > Priority: Critical > Labels: pull-request-available > > When querying the data from JDBC databases with custom schema containing > varchar I got this error : > {code:java} > [23/07/14 06:12:19 WARN TaskSetManager: Lost task 0.0 in stage 1.0 (TID 1) ( > executor 1): java.sql.SQLException: Unsupported type varchar(100) at > org.apache.spark.sql.errors.QueryExecutionErrors$.unsupportedJdbcTypeError(QueryExecutionErrors.scala:818) > 23/07/14 06:12:21 INFO TaskSetManager: Lost task 0.1 in stage 1.0 (TID 2) on > , executor 0: java.sql.SQLException (Unsupported type varchar(100)){code} > Code example: > {code:java} > CUSTOM_SCHEMA="ID Integer, NAME VARCHAR(100)" > df = spark.read.format("jdbc") > .option("url", "jdbc:oracle:thin:@0.0.0.0:1521:db") > .option("driver", "oracle.jdbc.OracleDriver") > .option("dbtable", "table") > .option("customSchema", CUSTOM_SCHEMA) > .option("user", "user") > .option("password", "password") > .load() > df.show(){code} > I tried to set {{spark.sql.legacy.charVarcharAsString = true}} to restore the > behavior before Spark 3.1 but it doesn't help. > The issue occurs in version 3.1.0 and above. I believe that this issue is > caused by https://issues.apache.org/jira/browse/SPARK-33480 -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org