我正在使用 SparkSQL 加载一堆 JSON 文件，但有些文件有问题。
我想继续处理其他文件，同时忽略坏文件，我该怎么做？
我尝试使用 try-catch 但它仍然失败。示例:
try {
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext._
val jsonFiles=sqlContext.jsonFile("/requests.loading")
} catch {
case _: Throwable => // Catching all exceptions and not doing anything with them
}
我失败了:
14/11/20 01:20:44 INFO scheduler.TaskSetManager: Starting task 3065.0 in stage 1.0 (TID 6150, HDdata2, NODE_LOCAL, 1246 bytes)<BR>
14/11/20 01:20:44 WARN scheduler.TaskSetManager: Lost task 3027.1 in stage 1.0 (TID 6130, HDdata2): com.fasterxml.jackson.core.JsonParseException: Unexpected end-of-input: was expecting closing quote for a string value
at [Source: java.io.StringReader@753ab9f1; line: 1, column: 1805]
最佳答案
如果您使用的是 Spark 1.2，Spark SQL 将为您处理那些损坏的 JSON 记录。这是一个例子...
// requests.loading has some broken records
val jsonFiles=sqlContext.jsonFile("/requests.loading")
// Look at the schema of jsonFiles, you will see a new column called "_corrupt_record", which holds all broken JSON records
// jsonFiles.printSchema
// Register jsonFiles as a table
jsonFiles.registerTempTable("jsonTable")
// To query all normal records
sqlContext.sql("SELECT * FROM jsonTable WHERE _corrupt_record IS NULL")
// To query all broken JSON records
sqlContext.sql("SELECT _corrupt_record FROM jsonTable WHERE _corrupt_record IS NOT NULL")
关于apache-spark - SparkSQL : Ignoring invalid json files，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/27035932/