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在IDEA中运行Scala脚本访问执行SparkSQL时：

df.show()

 

出现报错信息：

 1 19/12/06 14:26:17 INFO SparkContext: Created broadcast 2 from show at Student.scala:16  2 Exception in thread "main" org.apache.spark.sql.AnalysisException: Since Spark 2.3, the queries from raw JSON/CSV files are disallowed when the 3 referenced columns only include the internal corrupt record column 4 (named _corrupt_record by default). For example:  5 spark.read.schema(schema).json(file).filter($"_corrupt_record".isNotNull).count()  6 and spark.read.schema(schema).json(file).select("_corrupt_record").show().  7 Instead, you can cache or save the parsed results and then send the same query.  8 For example, val df = spark.read.schema(schema).json(file).cache() and then  9 df.filter($"_corrupt_record".isNotNull).count().; 10 at org.apache.spark.sql.execution.datasources.json.JsonFileFormat.buildReader(JsonFileFormat.scala:120) 11 at org.apache.spark.sql.execution.datasources.FileFormat$class.buildReaderWithPartitionValues(FileFormat.scala:129) 12 at org.apache.spark.sql.execution.datasources.TextBasedFileFormat.buildReaderWithPartitionValues(FileFormat.scala:165) 13 at org.apache.spark.sql.execution.FileSourceScanExec.inputRDD$lzycompute(DataSourceScanExec.scala:309) 14 at org.apache.spark.sql.execution.FileSourceScanExec.inputRDD(DataSourceScanExec.scala:305) 15 at org.apache.spark.sql.execution.FileSourceScanExec.inputRDDs(DataSourceScanExec.scala:327) 16 at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:627) 17 at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131) 18 at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127) 19 at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155) 20 at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) 21 at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152) 22 at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127) 23 at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247) 24 at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:339) 25 at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38) 26 at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3389) 27 at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550) 28 at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550) 29 at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370) 30 at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78) 31 at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125) 32 at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73) 33 at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3369) 34 at org.apache.spark.sql.Dataset.head(Dataset.scala:2550) 35 at org.apache.spark.sql.Dataset.take(Dataset.scala:2764) 36 at org.apache.spark.sql.Dataset.getRows(Dataset.scala:254) 37 at org.apache.spark.sql.Dataset.showString(Dataset.scala:291) 38 at org.apache.spark.sql.Dataset.show(Dataset.scala:751) 39 at org.apache.spark.sql.Dataset.show(Dataset.scala:710) 40 at org.apache.spark.sql.Dataset.show(Dataset.scala:719) 41 at Student$.main(Student.scala:16) 42 at Student.main(Student.scala)

 

因为我的JSON格式是多行的，只需要改为一行即可

{ "name": "Michael", "age": 12 } { "name": "Andy", "age": 13 } { "name": "Justin", "age": 8 }

 

修改为：

{"name": "Michael", "age": 12} {"name": "Andy", "age": 13} {"name": "Justin", "age": 8}