我有一个表，其中包含json对象和数组作为两个字段的数据类型。我在scala中的表模式类似
snSession.sql("CREATE TABLE subscriber_new14 (ID int,skills Map<STRING,INTEGER> ) USING column OPTIONS (PARTITION_BY 'ID',OVERFLOW 'true',EVICTION_BY 'LRUHEAPPERCENT' )");
我的java代码是
PreparedStatement s2 = snappy.prepareStatement("insert into APP.SUBSCRIBER_NEW11(ID ,SKILLS ) values(?,?)");
JSONObject obj = new JSONObject();
String str = obj.toString();
obj.put(1, 1);
obj.put(2, 2);
s2.setObject(26,obj);
l1= s2.executeBatch();
执行此时出现此错误
SEVERE: null
java.sql.SQLException: (SQLState=XCL12 Severity=20000) An attempt was made to put a data value of type 'org.json.simple.JSONObject' into a data value of type 'Blob' for column '26'.
at com.pivotal.gemfirexd.internal.shared.common.error.DefaultExceptionFactory30.getSQLException(DefaultExceptionFactory30.java:44)
at com.pivotal.gemfirexd.internal.shared.common.error.DefaultExceptionFactory30.getSQLException(DefaultExceptionFactory30.java:63)
at com.pivotal.gemfirexd.internal.shared.common.error.ExceptionUtil.newSQLException(ExceptionUtil.java:158)
at io.snappydata.thrift.common.Converters.newTypeSetConversionException(Converters.java:3014)
at io.snappydata.thrift.common.Converters.newTypeSetConversionException(Converters.java:3021)
at io.snappydata.thrift.common.Converters$14.setObject(Converters.java:2126)
at io.snappydata.thrift.common.Converters$21.setObject(Converters.java:2874)
at io.snappydata.thrift.internal.ClientPreparedStatement.setObject(ClientPreparedStatement.java:611)
at snappy.SnappyOps.upsert(SnappyOps.java:117)
at snappy.Mailthread.DataPush(Mailthread.java:55)
at snappy.Mailthread.run(Mailthread.java:36)
at java.lang.Thread.run(Thread.java:748)
Blob blob = snappy.createBlob();
blob.setBytes(1, str.getBytes());
所以我通过添加这个将json对象更改为blob类型
Blob blob = snappy.createBlob();
blob.setBytes(1, str.getBytes());
但当我通过从快速数据库检索时
从subscriber_new11限制10中选择技能；
快速数据因错误而停机
查询此时
`select skills from subscriber_new11 limit 10;`
获取错误
ERROR 38000: (SQLState=38000 Severity=20000) (Server=host1/103.18.248.32[1529] Thread=ThriftProcessor-0) The exception 'Job aborted due to stage failure: Task 0 in stage 18.0 failed 4 times, most recent failure: Lost task 0.3 in stage 18.0 (TID 29, host1, executor 103.18.248.32(332515):52609): java.lang.AssertionError: assertion failed
at scala.Predef$.assert(Predef.scala:156)
at org.apache.spark.sql.catalyst.util.SerializedMap.pointTo(SerializedMap.scala:78)
at org.apache.spark.sql.execution.row.ResultSetDecoder.readMap(ResultSetDecoder.scala:134)
at org.apache.spark.sql.execution.row.ResultSetDecoder.readMap(ResultSetDecoder.scala:32)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(generated.java:180)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenRDD$$anon$2.hasNext(WholeStageCodegenExec.scala:571)
at org.apache.spark.sql.execution.WholeStageCodegenRDD$$anon$1.hasNext(WholeStageCodegenExec.scala:508)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:389)
at org.apache.spark.sql.CachedDataFrame$.apply(CachedDataFrame.scala:451)
at org.apache.spark.sql.CachedDataFrame$.apply(CachedDataFrame.scala:409)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:95)
at org.apache.spark.scheduler.Task.run(Task.scala:126)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:326)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at org.apache.spark.executor.SnappyExecutor$$anon$2$$anon$3.run(SnappyExecutor.scala:57)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:' was thrown while evaluating an expression.
您可以参考示例中的JDBCWithComplexTypes.scala类，该类解释了如何使用JDBC客户端连接处理复杂的数据类型。在PreparedStatement中设置值之前，应使用ComplexTypeSerializer序列化数组对象。