I have raw data on a database with measurements on sensors a, b, c like this for example: unique_id;sensor;timestamp 111;A;2024-10-10 08:00:00.000000 222;C;2024-10-10 08:00:00.000000 333;A;2024-10-10 08:00:00.000000 444;A;2024-10-10 08:00:00.000000 555;A;2024-10-10 08:00:00.000000 666;C;2024-10-10 08:00:01.000000 777;C;2024-10-10 08:00:01.000000 888;C;2024-10-10 08:00:01.000000 555;B;2024-10-10 08:00:09.000000 111;A;2024-10-10 08:00:21.000000 444;A;2024-10-10 08:00:24.000000 444;A;2024-10-10 08:00:38.000000 444;B;2024-10-10 08:00:40.000000 666;C;2024-10-10 08:00:42.000000 111;C;2024-10-10 08:00:42.000000 444;B;2024-10-10 08:00:48.000000 111;C;2024-10-10 08:01:02.000000 666;C;2024-10-10 08:01:02.000000

I have created the external stage in Snowflake as below: CREATE or REPLACE STAGE sk_demo_stage URL='s3://raw-data/' FILE_FORMAT=(type = csv) STORAGE_INTEGRATION = s3_int DIRECTORY = ( ENABLE = TRUE); For a full load, I am using the below syntax: COPY INTO sk_demo.sk_schema.sk_employees FROM @sk_demo_stage/sample/employees; And since CDC is enabled for MySQL and the first column indicates

Let’s say I have three tables: t1: client_id transmission_id timestamp column_A 1 AAA1 2024-10-16 10:31:27 Banana 1 AAA2 2024-10-16 11:31:27 Citrus 2 BBB1 2024-10-16 09:12:14 Apple t2: client_id transmission_id timestamp column_B 1 AAA1 2024-10-16 10:41:27 Paris 1 AAA2 2024-10-16 11:41:27 London 2 BBB1 2024-10-16 09:22:14 NY t3: client_id transmission_id timestamp column_C 1 AAA1 2024-10-16 10:31:27

I have some data that looks like the below: id category sub_category sub_sub_category 1 Category 1 null null 1 Category 1 Subcategory 1 null 1 Category 1 Subcategory 1 SubSubCategory 1 1 Category 1 Subcategory 1 SubSubCategory 2 1 Category 2 Subcategory 2 SubSubCategory 2 I need it to look like this: id category sub_category

I need to parse the below XML to get the result in the form of the below table. I am getting NULL column without any data row. I am expecting below 3 rows with 3 columns. Kindly help thanks in advance. Required Output UNIFIER_US_XCPG1_VIEW 1 2024-10-16T08:36:53.000+00:00 UNIFIER_UXCORY_VIEW 5 2024-10-16T08:36:53.000+00:00 UNIFIER_UXBLS_VIEW 9 2024-10-16T08:36:53.000+00:00 Query: WITH tbl

This is my first time working with databases. I’m designing a database for an e-commerce project. I ended up with two versions of the schema, and I don’t know which one to go with or what its pros and cons are. V1: -- Person Schema create table person ( id serial primary key, name text

CREATE VIEW [dimension].[v_dim_customer] as SELECT — primary key KNA1.fk_MANDT_KUNNR AS sk_customer, KNA1.bk_MANDT_mandant, — attribut KNA1.[NAME1_nom], KNA1.[NAME2_nom_2], — KNA1.[DEAR1_concurrents], –KNA1.[DEAR2_responsable_adv], ----- /*flag client interne/externe*/----- flag_ext_int.externe_interne_code, /* flag client interne/externe niveau 2 (détaillé : intra groupe / intra société / externe)*/ flag_ext_int.externe_interne_level_2_code, -- date pour delta --CY.max_slt_datetime -- add --18/12/2023 FROM [e3p].[KNA1] KNA1 LEFT OUTER JOIN [e3p].T005T

Need help in understanding which of the following snowflake SQL is faster and why. provided tablea has 50 columns. Or do You think both are equally efficient. select col1, col2 from (select * from tablea /*AdditionalLogc*/)) --Vs select col1, col2 from (select col1, col2 from tablea /*AdditionalLogc*/)) You need to sign in to view this

I have a ‘column specifier’ table that specifies the names of 1 or more columns of a source table that contain the data needed for stuff. The list of columns required depends on various things, but here, it depends only on what I’m calling the ‘cid’. I must retrieve the values found in each column

I am trying to create a SQL query to count active transactions month by month from a transaction_status table. Each transaction_id can have multiple statuses, with two key statuses: ENDORSEMENT_SUCCESS (when the transaction is active) and ENDORSEMENT_CLOSED_SUCCESS (when the transaction is closed). Problem: The challenge I’m facing is ensuring that: A transaction should only be