![]() ![]() To access the records inside, you have to: Result: Querying JSON array (REPEATED RECORD fields)Īs briefly mentioned above, REPEATED RECORD field is an array that hold multiple records in a single row. You can chain your dot notation to query deeper field values, for example. You can simply use the dot notations to access the child columns: #standardsql Querying single (non-repeated) RECORD field is like querying key-value JSON objects. In this case, the RECORD field will have REPEATED mode: `hits` is a REPEATED RECORD field Querying key-value JSON object (non-repeated RECORD field) Your RECORD column can have a simple nested structure (each row only holds a single record), or it can hold nested and repeated data (each row holds multiple records). ![]() Ease of use: You can use dot notation ( parent_col.child_col) to query from RECORD columns, which is quite convenient.Performance: You can selectively scan child columns instead of scanning the whole parent RECORD column, which will save you query money.Consistency: Your future data is made sure to conform to the pre-defined structure → not have to worry that a valid query today will be invalid tomorrow.On the other hand, the explicit structure brings you several benefits: For example, this is from the Create table dialogue in BigQuery: Define the table schema, including schema of nested fields Storing your data in RECORD columns takes a bit more effort as you need to define the data structure up-front when creating your table. A column of RECORD type is in fact a large column containing multiple child columns. While PostgreSQL and MySQL have JSON type, BigQuery uses the RECORD (or STRUCT) type to represent nested structure. Handling BigQuery's JSON data as RECORD type What is RECORD type? Let's call this "stringified JSON".Įach scenario needs to be handled differently as follow. In a column of type "STRING": The JSON value is treated just like a normal string that happens to have JSON format.In a column of type "RECORD": This data type is specifically designed to store nested structure data (JSON) in BigQuery.In BigQuery, JSON data may be stored in two ways: ![]() All queries are written with BigQuery's #StandardSQL mode. The examples below use the ga_sessions sample dataset provided by Google. Beside some obvious naming and syntax differences, you can apply the same approaches to handle nested data in many other SQL databases like PostgreSQL, MySQL. In this article, we will show you how to handle nested data in BigQuery. Yet if done well, nested data structure (JSON) is a very powerful mechanism to better express hierarchical relationships between entities comparing to the conventional flat structure of tables. Working with nested JSON data in BigQuery analytics database might be confusing for people new to BigQuery. ![]()
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