Note that the above example loads the JSON file into a single column (each record in a JSON file loads into a single column of a row. Conclusion To load a JSON file into the Snowflake table, you need to upload the data file to Snowflake internal stage and then load the file from th...
You can seamlessly utilize SQL commands to perform bulk-loading into Snowflake with the powerful SnowSQL client. This method is limited to loading data from typical delimited plain-text files like Comma-delimited CSVs and from a spectrum of semi-structured sources—JSON, AVRO, Parquet, or ORC ...
For ease of readability, it’s generally easier to create a string variable for the query we want to run. For larger queries, using three double quotes"""query"""instead of just double quotes"query”, enables the query to neatly span multiple lines like in the gist above. Now we can u...
Execute the Snowflake query and fetch the results. Connect to SharePoint using a suitable API or library. Prepare the query results for upload by converting them to a compatible format (e.g., CSV, Excel, JSON). Upload the prepared data to the SharePo...
Snowflake Task 2: This layer will convert the raw JSON document into reporting tables that the analytics team can easily query. To convert JSON documents into structured format, the lateral flatten feature of Snowflake can be used. Lateral flatten is an easy-to-use function that explodes the ...
I would like to insert the data from copy activity (REST API as source) to Snowflake table (Sink). While using the mapping provided by copy activity is giving option to map all the elements in the nested JSON to columns in table. In the below example,
As shown in the tutorial, querying JSON columns is fairly straightforward. However, it can get a bit difficult to query nested JSON structures. It is important to use appropriate JSON operators and functions to navigate and query nested JSON objects and arrays. Functions like->,->>,#>, and...
I’ve been saying document databases over and over up to this point, but what actually are they? Here are the main concepts: Documents: data is stored in objects called documents. In simple terms, documents are similar to JSON key-value objects. A single document is equivalent to a row ...
Ease of use: Snowflake offers an easy-to-use interface and supports standard SQL queries. This makes it accessible to users with knowledge of SQL, allowing them to query and analyse data without the need to learn a new language or complex procedures. ...
Learn how to query JSON objects in SQL Server. This tutorial covers SQL Server's JSON querying capabilities, from extracting specific JSON values to filtering data based on JSON properties. Master the art of handling unstructured data with SQL Server's J