[GitHub] [iceberg] kbendick edited a comment on issue #3585: Spark 3.2.0 java.lang.IncompatibleClassChangeError when using IcebergSparkSessionExtensions

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kbendick edited a comment on issue #3585:
URL: https://github.com/apache/iceberg/issues/3585#issuecomment-1021743093


   From Spark 3.2, I also used a partitioned table to test dynamic partition overwrite in Spark 3.2
   
   Bash start up script from spark-3.2.0-bin-hadoop3.2:
   ```bash
   mkdir -p /tmp/iceberg/warehouse && ./bin/spark-shell \
   --packages 'org.apache.iceberg:iceberg-spark-runtime-3.2_2.12:0.13.0' \
   --repositories https://repository.apache.org/content/repositories/orgapacheiceberg-1079/  \
   --conf spark.sql.extensions=org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions \
   --conf spark.sql.catalog.local=org.apache.iceberg.spark.SparkCatalog  \
   --conf spark.sql.catalog.local.type=hadoop \
   --conf spark.sql.catalog.local.warehouse=/tmp/iceberg/warehouse \
   --conf spark.sql.sources.partitionOverwriteMode=dynamic
   ```
   
   Spark Shell:
   ```scala
   scala> spark.sql("CREATE TABLE local.db.table_partitioned (id bigint, data string) USING iceberg partitioned by (id)")
   res6: org.apache.spark.sql.DataFrame = []
   
   scala> spark.sql("show tables in local.db").show
   +---------+-----------------+-----------+
   |namespace|        tableName|isTemporary|
   +---------+-----------------+-----------+
   |       db|table_partitioned|      false|
   |       db|            table|      false|
   +---------+-----------------+-----------+
   
   scala> spark.sql("INSERT INTO local.db.table_partitioned(id, data) VALUES (1, 'Hank'), (2, 'Kyle'), (3, 'Jethro'), (4, 'Russell'), (5, 'Maggie')")
   
   scala> spark.sql("select * from local.db.table_partitioned").show
   +---+-------+
   | id|   data|
   +---+-------+
   |  1|   Hank|
   |  2|   Kyle|
   |  3| Jethro|
   |  4|Russell|
   |  5| Maggie|
   +---+-------+
   
   scala> spark.createDataFrame(Seq((3, "Burt"))).toDF("id", "data").write.mode("overwrite").insertInto("local.db.table_partitioned")
   
   scala> spark.sql("select * from local.db.table_partitioned order by id").show
   +---+-------+
   | id|   data|
   +---+-------+
   |  1|   Hank|
   |  2|   Kyle|
   |  3|   Burt|
   |  4|Russell|
   |  5| Maggie|
   +---+-------+
   ```


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