Syntax

LOAD DATA [LOCAL] INFILE 'file_name'
  [REPLACE | SKIP { CONSTRAINT | DUPLICATE KEY } ERRORS]
  INTO TABLE tbl_name
  FORMAT JSON
  subvalue_mapping
  [SET col_name = expr,...]
  [WHERE expr,...]
  [MAX_ERRORS number]
  [ERRORS HANDLE string]

subvalue_mapping:
  ( {col_name | @variable_name} <- subvalue_path [DEFAULT literal_expr], ...)

subvalue_path:
  {% | [%::]ident [::ident ...]}

Semantics

Error Logging and Error Handling are discussed in the LOAD DATA page.

Extract specified subvalues from each JSON value in file_name. Assign them to specified columns of a new row in tbl_name, or to variables used for a column assignment in a SET clause. If a specified subvalue can’t be found in an input JSON, assign the DEFAULT clause literal instead. Discard rows which don’t match the WHERE clause.

To specify the compression type of an input file, use the COMPRESSION clause. See LOAD DATA for more information.

The file named by file_name must consist of concatenated UTF-8 encoded JSON values, optionally separated by whitespace. Newline-delimited JSON is accepted, for example.

Non-standard JSON values like NaN, Infinity, and -Infinity must not occur in file_name.

If file_name ends in .gz or .lz4, it will be decompressed.

JSON LOAD DATA supports a subset of the error recovery options allowed by CSV LOAD DATA. Their behavior is as described under Load CSV Files with LOAD DATA.

Like CSV LOAD DATA, JSON LOAD DATA allows you to use globbing to load data from multiple files.

Writing to multiple databases in a transaction is not supported.

LOAD DATA from an AWS S3 Source

JSON files that are stored in an AWS S3 bucket can be loaded via a LOAD DATA query without a pipeline.

LOAD DATA S3 '<bucket name>'
CONFIG '{"region" : "<region_name>"}' 
CREDENTIALS '{"aws_access_key_id" : "<key_id>", 
             "aws_secret_access_key": "<access_key>"}' 
INTO TABLE <table_name>;

For more information on loading data from an AWS S3 bucket, refer to .