Snowflake has introduced innovative SQL techniques that will significantly simplify tasks for coders. Over the past three decades, SQL has established itself as the standard language for data interaction. Hence, we must embrace these new and improved versions of SQL to streamline our daily operations effectively.
In this article, we will go through these new syntaxes one by one with examples and use cases.
Let’s create a STUDENT table in the snowflake as below before looking into these new syntaxes.
CREATE DATABASE IF NOT EXISTS DB_TEST;
CREATE SCHEMA IF NOT EXISTS DB_TEST.TEST;
CREATE TABLE IF NOT EXISTS DB_TEST.TEST.STUDENT
(
ID NUMBER,
STUDENT_NAME VARCHAR,
SUBJECT VARCHAR,
MARKS NUMBER
);
INSERT INTO DB_TEST.TEST.STUDENT
VALUES
(1,'as','math',90),
(2,'kp','math',23),
(3,'sp','math',76),
(4,'dp','science',89),
(1,'as','science',43),
(2,'kp','science',12),
(3,'sp','science',45),
(4,'dp','math',98);
SELECT * FROM DB_TEST.TEST.STUDENT;
LIKE ALL
Enables case-sensitive string matching by comparing it with one or multiple patterns. In the general LIKE operation, you can compare strings with only one pattern but with LIKE All you can compare…
