![]() ![]() '$.data.customers#."phone numbers"#. All nested path prefixes ending with a '#' character must be a prefix of the longest nested path.ĬREATE OR REPLACE TABLE json_input2(id INT, json VARCHAR( 2000000)).To extract several rows, the json_path_expr has to contain a '#' character to split up all expressions identified by a nested path into several rows. This makes it possible to create an extra row for each element in a JSON array. With JSON_EXTRACT, it is possible to extract several rows from a single json_expr.To know more about the different possible errors, refer to the JSON Error Handling section.If the error behavior for a path is LOG ON ERROR and an error occurs during the JSON processing, JSON_EXTRACT returns NULL for the path and writes the problem into the 'error column'.If the error behavior for a path is LOG ON EMPTY and the path does not identify an SQL value, JSON_EXTRACT returns NULL for the path and writes the problem into the 'error column'.To specify the ON EMPTY and ON ERROR behavior for each path separately, refer to the JSON Path Expressions section.It is possible to freely choose the column_name and (VAR)CHAR size for the 'error column' in the EMITS clause. If '$.error()' is present, the EMITS clause requires an extra 'error column' with data_type (VAR)CHAR to log all occurring errors.If the last json_path_expr parameter is the string literal '$.error()', the error behavior of JSON_EXTRACT changes to LOG ON EMPTY and LOG ON ERROR for all json_path_expr parameters.Thus, ERROR ON ERROR is the default for each json_path_expr. If any error occurs during the JSON processing, JSON_EXTRACT throws an error by default.Thus, ERROR ON EMPTY is the default for each json_path_expr. ![]() If any json_path_expr does not identify an SQL value, JSON_EXTRACT throws an error.Thus, the first column_name and data_type belongs to the first json_path_expr. The order of the columns in the EMITS clause corresponds to the order of the json_path_expr parameters. Note the following considerations of SUPER configurations when you use Amazon Redshift SUPER data type and PartiQL. For each json_path_expr, the EMITS clause has to define a column_name and a data_type for the JSON values it returns. JSON_EXTRACT supports an arbitrary number of json_path_expr parameters.For the path syntax rules in Exasol, refer to the JSON Path Expressions section. The function accepts an arbitrary expression of type (VAR)CHAR for each path. Each json_path_expr parameter defines a single JSON path for JSON_EXTRACT.Although JSON_EXTRACT relies on the UDF framework, internally, it uses a fast native JSON processing framework. Thus, the same restrictions apply (for example, there is no Virtual Schema pushdown). JSON_EXTRACT is based on the Exasol UDF framework and behaves like a SCALAR EMITS UDF.To return an SQL value, json_expr has to follow the syntax rules on. Exasol accepts an arbitrary expression of type (VAR)CHAR. The parameter json_expr defines the input JSON string for the function. ![]()
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