Best practices for reading JSON data - Amazon Athena
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Best practices for reading JSON data

JavaScript Object Notation (JSON) is a common method for encoding data structures as text. Many applications and tools output data that is JSON-encoded.

In Amazon Athena, you can create tables from external data and include the JSON-encoded data in them. For such types of source data, use Athena together with JSON SerDe libraries.

Use the following tips to read JSON-encoded data:

  • Choose the right SerDe, a native JSON SerDe,, or an OpenX SerDe, For more information, see JSON SerDe libraries.

  • Make sure that each JSON-encoded record is represented on a separate line, not pretty-printed.


    The SerDe expects each JSON document to be on a single line of text with no line termination characters separating the fields in the record. If the JSON text is in pretty print format, you may receive an error message like HIVE_CURSOR_ERROR: Row is not a valid JSON Object or HIVE_CURSOR_ERROR: JsonParseException: Unexpected end-of-input: expected close marker for OBJECT when you attempt to query the table after you create it. For more information, see JSON Data Files in the OpenX SerDe documentation on GitHub.

  • Generate your JSON-encoded data in case-insensitive columns.

  • Provide an option to ignore malformed records, as in this example.

    CREATE EXTERNAL TABLE json_table ( column_a string, column_b int ) ROW FORMAT SERDE '' WITH SERDEPROPERTIES ('ignore.malformed.json' = 'true') LOCATION 's3://DOC-EXAMPLE-BUCKET/path/';
  • Convert fields in source data that have an undetermined schema to JSON-encoded strings in Athena.

When Athena creates tables backed by JSON data, it parses the data based on the existing and predefined schema. However, not all of your data may have a predefined schema. To simplify schema management in such cases, it is often useful to convert fields in source data that have an undetermined schema to JSON strings in Athena, and then use JSON SerDe libraries.

For example, consider an IoT application that publishes events with common fields from different sensors. One of those fields must store a custom payload that is unique to the sensor sending the event. In this case, since you don't know the schema, we recommend that you store the information as a JSON-encoded string. To do this, convert data in your Athena table to JSON, as in the following example. You can also convert JSON-encoded data to Athena data types.

Converting Athena data types to JSON

To convert Athena data types to JSON, use CAST.

WITH dataset AS ( SELECT CAST('HELLO ATHENA' AS JSON) AS hello_msg, CAST(12345 AS JSON) AS some_int, CAST(MAP(ARRAY['a', 'b'], ARRAY[1,2]) AS JSON) AS some_map ) SELECT * FROM dataset

This query returns:

+-------------------------------------------+ | hello_msg | some_int | some_map | +-------------------------------------------+ | "HELLO ATHENA" | 12345 | {"a":1,"b":2} | +-------------------------------------------+

Converting JSON to Athena data types

To convert JSON data to Athena data types, use CAST.


In this example, to denote strings as JSON-encoded, start with the JSON keyword and use single quotes, such as JSON '12345'

WITH dataset AS ( SELECT CAST(JSON '"HELLO ATHENA"' AS VARCHAR) AS hello_msg, CAST(JSON '12345' AS INTEGER) AS some_int, CAST(JSON '{"a":1,"b":2}' AS MAP(VARCHAR, INTEGER)) AS some_map ) SELECT * FROM dataset

This query returns:

+-------------------------------------+ | hello_msg | some_int | some_map | +-------------------------------------+ | HELLO ATHENA | 12345 | {a:1,b:2} | +-------------------------------------+