parseJsonTable

Syntax

Arguments

• json is a STRING scalar or vector containing JSON objects. If it is a STRING scalar, it can contain one or more JSON objects. JSON arrays and recursive JSON objects are not supported yet.

• schema (optional) is a table that specifies the column names and types. It can contain the following columns:

  Column	Description
  name	a string representing the column name
  type	a string representing the column type. Currently, BLOB is not supported.
  format (optional)	a string specifying the format of date or time columns.

  If schema is not specified, the function will automatically parse the schema based on the first 10 JSON objects.

• keyCaseSensitive (optional) indicates whether keys are case-sensitive. true (default) means case sensitive, false means case insensitive.

Details

Parses JSON objects into an in-memory table.

• When json is a string containing multiple JSON objects, each object will be converted to a row in the table.
• When json is a vector of strings, each element will be converted to a row in the table.

Examples

json1='{"ID":1, "NAME":"cc"}{"NAME":"dd"}'
parseJsonTable(json1)

output:

json2 = '{"col_test":"20190522150407"}'
schemaTB = table(["col_test"] as name, ["DATETIME"] as type, ["yyyyMMddHHmmss"] as format)
parseJsonTable(json2, schemaTB)

output: 2019.05.22T15:04:07

json3='{"ID":11, "NAME":"dd"}'
schemaTB1 = table(["ID", "NAME", "col_test"] as name, ["INT", "STRING", "DATETIME"] as type, [,,"yyyyMMddHHmmss"] as format)
parseJsonTable(concat([json2,json3]),schemaTB1)            

When json is a STRING vector:

parseJsonTable([json2,json3],schemaTB1)

output: