![]() ![]() My task was to figure out how many (and where) components have primary key columns in output mapping set to non-existing column. So let's have a look at my recent use case. Snowflake has made working with semi-structured data a cinch In this blog, Iâll walk through how to query and create tables in Snowflake using data in the JSON format. One less thing to worry about that Snowflake takes care of. DecemFAQ Snowflake optimized query performance on JSON by extracting as many JSON elements as columnar form, which means those extracted elementsâ metadata will be collected. Map bindValues.The JSONVALUE function is used to extract content from JSON documents using a. default to snowflake (a special json format for snowflake query result. ![]() Snowflake offers VARIANT data type for storing structured data (like JSON and some others), but for my ad-hoc processing I am usually too lazy to worry about data types, and I store everything as VARCHAR (or STRING) and cast the correct data type on the fly. jOOQ, a fluent API for typesafe SQL query construction and execution. I won't elaborate much on what Snowflake is, but for the context of this post let's say it's a modern maintenance-free database, that separates storage from computing, and is capable of joining JSON data with flat tables. Ad hoc querying of this sort of data is painful, let alone if you need to join relational data to it. It often contains data structures that are not easy to map to a relational/flat structure and their structure is not fixed by any means. Statistical operators for events and properties. 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).Sometimes I end up with a serialized JSON stored in a relational database (or in a CSV file). client.extractschemafromsource(snowflaketable) Create a snowflake query source snowflakequery SnowflakeTable(. Transform and enrich data at query time without engineering resources.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') There are a few Community articles where we have examples of doing this. ![]() 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. Looker doesn't have a native JSON field type. What is Snowflake Why Query Snowflake JSON Data How does Snowflake handle Snowflake JSON Objects Working with Snowflake JSON. An expression of type VARIANT that holds valid JSON information. ![]()
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