Let’s understand what we mean when we use the term ‘ Semi-structured data’. Semi-structured ( such as JSON, Avro, ORC, Parquet and XML ).Structured (Data in Tabular format such as csv etc.Spark & Snowflake both, have capabilities to perform data analysis on different kinds of data like, On the other hand, Snowflake is a data warehouse that uses a new SQL database engine with a unique architecture designed for the cloud such as AWS and Microsoft Azure. In the Big Data world, Apache Spark is an open-source, scalable, massively parallel, in-memory execution, distributed cluster-computing framework which provides faster and easy-to-use analytics along with capabilities like Machine Learning, graph computation and stream processing using programming languages like Scala, R, Java and Python. "COLUMN_PATH": "_DATE.Before we delve deeper into the differences between processing JSON in Spark vs Snowflake, let’s understand the basics of Cloud Service/Framework. JOIN TABLES_JSON ON TABLES_JSON.TABLE_PATH = COLUMNS_JSON.TABLE_PATH 'COLUMNS',ARRAY_AGG(OBJECT_CONSTRUCT(COLUMNS_JSON.*))) 'AUTO_CLUSTERING_ON',TABLES_JSON.AUTO_CLUSTERING_ON, 'CLUSTERING_KEY',TABLES_JSON.CLUSTERING_KEY, 'TABLE_SCHEMA', TABLES_JSON.TABLE_SCHEMA, 'TABLE_CATALOG', TABLES_JSON.TABLE_CATALOG, WHERE TABLE_NAME IN(SELECT TABLE_NAME FROM SNOWFLAKE.ACCOUNT_USAGE.TABLES WHERE TABLE_SCHEMA != 'INFORMATION_SCHEMA' AND DELETED IS NULL) TABLE_CATALOG || '.' || TABLE_SCHEMA || '.' || TABLE_NAME || '.' || COLUMN_NAME AS COLUMN_PATH, TABLE_CATALOG || '.' || TABLE_SCHEMA || '.' || TABLE_NAME AS TABLE_PATH, WHERE TABLE_SCHEMA != 'INFORMATION_SCHEMA' AND DELETED IS NULL), SELECT TABLE_CATALOG || '.' || TABLE_SCHEMA || '.' || TABLE_NAME AS TABLE_PATH, "COLUMN_PATH": "_DATE.QUARTER_NAME_FULL", Doing all this over billions of rows, in seconds, in AWS, GCP or Azure all over the globe.You can copy data into cloud storage of your choice using COPY INTO as UNLOAD.Then there is this little gem of function for handling one to many nestings ARRAY_AGG(*).Even better you can turn any row or result set into a JSON Document with OBJECT_CONSTRUCT(*).You can turn any row or result set into an Array with ARRAY_CONSTRUCT(*).I have started playing around with deeper topics on JSON write at massive scale. Snowflake can read and query JSON better than any SQL Language on the planet, and it’s got me hooked. Storing the JSON in a column in the same table with traditional columns the long tail of fields people never query.Storing the JSON in a column in the same table with traditional columns for schema evolution.
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