Reading JSON with Apache Spark – `corrupt_record`

by

As Spark expects “JSON Line format” not a typical JSON format, we can tell spark to read typical JSON by specifying:

val df = spark.read.option("multiline", "true").json("<file>")

More Related Contents:

  1. how to convert json string to dataframe on spark
  2. Spark Row to JSON
  3. What JSON library to use in Scala? [closed]
  4. How to parse JSON in Scala using standard Scala classes?
  5. Read multiline JSON in Apache Spark
  6. Defaults for missing properties in play 2 JSON formats
  7. How to turn json to case class when case class has only one field
  8. No Json serializer as JsObject found for type play.api.libs.json.JsObject
  9. Small Example of Jackson Scala Module?
  10. Importing local json file using d3.json does not work
  11. JSON Invalid UTF-8 middle byte
  12. Automatically and Elegantly flatten DataFrame in Spark SQL
  13. JSON Naming Convention (snake_case, camelCase or PascalCase) [closed]
  14. How to import JSON File into a TypeScript file?
  15. Defining a UDF that accepts an Array of objects in a Spark DataFrame?
  16. Spark / Scala: forward fill with last observation
  17. UnicodeDecodeError: ‘utf8’ codec can’t decode byte 0x80 in position 3131: invalid start byte
  18. Standard way of referencing an object by identity (for, eg, circular references)?
  19. Apache Spark: Get number of records per partition
  20. How to generate JSON response from JSF?
  21. How to output Django queryset as JSON?
  22. Flutter Registration with API
  23. How to save an array as a json file in Swift?
  24. How to get keys and values from MapType column in SparkSQL DataFrame
  25. JSON Parsing in Swift 3
  26. Create JSON using jq from pipe-separated keys and values in bash
  27. How to sort an RDD in Scala Spark?
  28. Laravel: validate json object
  29. Call json.Unmarshal inside UnmarshalJSON function without causing stack overflow
  30. In postgresql, how can I return a boolean value instead of string on a jsonb key?

Leave a Comment