Error when insert `Array(String)` in Spark

[pan3793]

Error when insert Array(String) in Spark

CREATE TABLE xm_terms (
  create_time       DateTime('Asia/Shanghai'),
  update_time       DateTime('Asia/Shanghai') COMMENT 'keep the larger record when merge',
  project_id        String                    COMMENT 'pk_1',
  project_version   String                    COMMENT 'pk_2',
  worktable_id      Nullable(String)          COMMENT 'not used in ck, keep it to compatible with Druid',
  worktable_version Nullable(String)          COMMENT 'not used in ck, keep it to compatible with Druid',
  seq               Int64                     COMMENT 'pk_3',
  ref_col_name      String                    COMMENT 'pk_4, ref xm_fact column name',
  terms             Array(String)
) ENGINE = ReplacingMergeTree("update_time")
ORDER BY (project_id, project_version, seq, ref_col_name)
PARTITION BY toYYYYMM(create_time);

Lost task 0.0 in stage 14.0 (TID 294, cdh-worker004, executor 1): java.lang.IllegalArgumentException: Can't get JDBC type for array<string>
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$getJdbcType$2.apply(JdbcUtils.scala:183)
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$getJdbcType$2.apply(JdbcUtils.scala:183)
	at scala.Option.getOrElse(Option.scala:121)
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$getJdbcType(JdbcUtils.scala:182)
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$20.apply(JdbcUtils.scala:645)
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$20.apply(JdbcUtils.scala:645)
	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
	at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
	at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
	at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
	at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:186)
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:645)
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:834)
	at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:834)
	at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$28.apply(RDD.scala:935)
	at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$28.apply(RDD.scala:935)
	at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2121)
	at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2121)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
	at org.apache.spark.scheduler.Task.run(Task.scala:121)
	at org.apache.spark.executor.Executor$TaskRunner$$anonfun$11.apply(Executor.scala:407)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1408)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:413)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	at java.lang.Thread.run(Thread.java:748)