Generate query functions by using the --sql flag on prisma generate: Import the query function from @prisma/client/sql ⦠⦠and call it inside the new $queryRawTyped function to get fully typed results ð If your SQL query has arguments, they are provided to the query function passed to $queryRawTyped The Prisma Client API together with TypedSQL provides the best experience for both CRUD operations
SELECT 1 SELECT 1 + 2 SELECT LEN("Git Query Language") SELECT "One" IN ("One", "Two", "Three") SELECT "Git Query Language" LIKE "%Query%" SET @arr = [1, 2, 3]; SELECT [[1, 2, 3], [4, 5, 6], [7, 8, 9]]; SELECT @arr[1], @arr[2], @arr[3], ARRAY_LENGTH(@arr); SELECT @arr[1:2], @arr[2:], @arr[:2]; SELECT DISTINCT title AS tt FROM commits SELECT author_name, COUNT(author_name) AS commit_num FROM commits
SQL:2023 has been wrapped. The final text has been submitted by the working group to ISO Central Secretariat, and itâs now up to the ISO gods when it will be published. Based on past experience, it could be between a few weeks and a few months. In the meantime, we can look at what is new. The changes can be grouped into three areas: Various smaller changes to the existing SQL language New features
Amazon Redshift now supports new SQL functionalities including ROLLUP, CUBE, and GROUPING SETS, to simplify building multi-dimensional analytics applications. ROLLUP, CUBE, and GROUPING SETS simplifies data warehouse migrations by offering the commonly used syntax across databases. Multi-dimensional analysis requires you to build complex processes and queries to aggregate and analyze core business
SQLAlchemy 2.0.0, the first production release of SQLAlchemy 2.0, is now available. With this release, the default version of SQLAlchemy that will install when one runs pip install sqlalchemy will be version 2.0. Note that version 2.0 has significant API changes compared to the 1.4 series, so applications that run on the 1.x series of SQLAlchemy which have not gone through the migration process sh
Gazette makes it easy to build platforms that flexibly mix SQL, batch, and millisecond-latency streaming processing paradigms. It enables teams, applications, and analysts to work from a common catalog of data in the way that's most convenient to them. Gazette's core abstraction is a "journal" -- a streaming append log that's represented using regular files in a BLOB store (i.e., S3). The magic of
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