![]() ![]() Set default value of overwrite option to true for put command, if overwrite option is not specified in the sql command.ĬLIENT_ENABLE_LOG_INFO_STATEMENT_PARAMETERSĮnable info-level logging for Prepared Statement binding parameters This parameter is for Snowflake use only.Įnables conservative memory usage for JDBC Whether auto-commit feature is enabled for this client. If auto-commit is false, then an explicit commit or rollback is required to close a transaction. If auto-commit is set to true, then a statement that requires a transaction is executed within a transaction implicitly. ![]() The auto-commit property determines whether statement should be implicitly wrapped within a transaction or not. If true, Snowflake will automatically abort queries when it detects that the client has disappeared. Use the following command to show all the parameters provided by snowflake −įollowing are the few details which can be viewed by just running the query "SHOW PARAMETERS " Sr.No Use the following command to see all the columns − Results provide timestamp, username, how login has done either using password or SSO, errors during login etc. Select * from table(test_db.information_schema.login_history()) Use the following query to find the login history of a database − Select * from table(result_scan(last_query_id())) JOIN snowflake_sample_data.tpch_sf1.nation SELECT * FROM snowflake_sample_data.tpch_sf1.region To check variables, run following queries in sequence − Use the following query to check stages and file format created in Snowflake − SELECT * FROM TABLE (INFORMATION_SCHEMA.DATABASE_STORAGE_USAGE_HISTORY Use the following query to display the usage of last 10 days. This query will display only the first 10 rows. Use the following query to bring limited data in Select statement − In the first example, we'll use the FLATTEN command to access a nested object.In this chapter, we will some sample useful queries in Snowflake and their outputs. To illustrate how the FLATTEN command works, let's look at a few examples. This makes it easy to access specific data without having to traverse the entire object. The FLATTEN command also allows you to specify a path to the data you want to access. This flattened version makes it easier to access the data you need, as it removes the need to traverse the object's hierarchy. It takes a JSON object as an argument and returns a flattened version of the object. The FLATTEN command is a Snowflake function that allows you to query nested JSON data. In this article, we'll look at how to use the FLATTEN command to query JSON data. It allows you to easily access nested data, and it can be used to quickly extract the data you need. Snowflake's FLATTEN command is a powerful tool for querying JSON data. But querying JSON data can be tricky, as it's not always easy to access the data you need. It's a lightweight format that is easy to read and write, and it's becoming the go-to format for many web applications. JSON data is becoming increasingly popular as a way to store and share data. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |