Following is the syntax for TOJSON function. For example, Snowflake supports TOJSON and PARSEJSON functions to convert and validate json values. jsonlateral flattensemi-structured dataSnowflakeZero. Here is a cool open-source Python script which uses the Looker API to automatically detect JSON fields in the underlying database table and generates LookML for them (this is specific to Snowflake connections and may require adjusting to fit your use case). Similar to many relational databases, Snowflake supports built-in functions that you can use to convert the string containing json representation to json format. Zero to Snowflake: Loading and Querying Semi-Structured JSON Data. NOTE: in BigQuery a JSON path must start with a $ followed by the index position and the string to parse, like: JSON_EXTRACT($.temperature_alerts, '$.description') Snowflake allows you to specify a sub-column within a parent column, which Snowflake dynamically derives from the schema definition embedded in the JSON data. This notation is similar to the familiar SQL lumn notation. There are a few Community articles where we have examples of doing this. The query uses the src:devicetype notation to specify the column name and the JSON element name to retrieve. You'll want to use JSON parsing functions in SQL, like json_extract_path in Postgres and JSON_EXTRACT in BigQuery to extract the JSON and put it into a type that Looker can accept, like a string. Here we learned to query JSON data from the table in Snowflake.Looker doesn't have a native JSON field type. The output of the query: As you can see, in the below image, we are select the individual attributes from the JSON object and create columns. Here we are going to query the JSON object using the select statement as shown below.ĭEZYRE_CUSTOMER_DATA:address.city::string as City,ĭEZYRE_CUSTOMER_DATA:address.state::string as state,ĭEZYRE_CUSTOMER_DATA:address.streetAddress::string as streetNo Here we will verify the data loaded into the target table by running a select query as shown below. Here we will load the JSON data to the target table, which we loaded earlier into the internal stage, as shown below. Consequently, without needing to perform any changes, you may query this data. Put file://D:\customer.json output of the statement: You can simply import JSON data into relational tables using Snowflake JSON. Here we will load the JSON data file from your local system to the staging of the Snowflake as shown below. ) ] Ĭreate or replace temporary table dezyre_customer_table (dezyre_customer_data variant ) It creates a new table in the current/specified schema or replaces an existing table.ĬREATE TABLE. Here we are going to create a temporary table using the Create statement as shown below. Step 5: Create Table in Snowflake using Create Statement What is Snowflake Why Query Snowflake JSON Data How does Snowflake handle Snowflake JSON Objects Working with Snowflake JSON. TYPE = ]Ĭreate temporary stage custome_temp_int_stage To select the database which you created earlier, we will use the "use" statementĬreates a named file format that describes a set of staged data to access or load into Snowflake tables.ĬREATE FILE FORMAT Follow the steps provided in the link above. Go to and then log in by providing your credentials. We need to log in to the snowflake account. Steps to connect to Snowflake by CLI Click Here.Steps to create Snowflake account Click Here.Step 7: Copy the data into Target Table.Step 6: Load JSON file to internal stage.Step 5: Create Table in Snowflake using Create Statement.Recipe Objective: How to query JSON data from the table in Snowflake?.
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