SQL should be your default choice for data engineering pipelines

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  This dbt package contains macros to support unit testing that can be (re)used across dbt projects.

  

> How do you test some SQL logic in isolation?

I do this using sql

1. Extracting an 'ephemeral model' to different model file

2. Mock out this model in upstream model in unit tests https://github.com/EqualExperts/dbt-unit-testing

3. Write unit tests for this model.

This is not different than regular software development in a language like java.

I would argue its even better better because unit tests are always in tabular format and pretty easy to understand. Java unit tests on other hand are never read by devs in practice.

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  Java client and JDBC driver for ClickHouse

  

Agree with the OP that SQL will almost assuredly still be in use for 20+ years in the future, given the simplicity and flexibility of the declarative language, standardization, and as applicable to today as it was then to our big data problems.

Any discussion of SQL at scale must include ClickHouse [https://clickhouse.com/docs/en/install#self-managed-install], given it's broad open-source use, integrations available for Spark with JDBC [https://github.com/ClickHouse/clickhouse-jdbc/] or the open-source Spark-ClickHouse Connector [https://github.com/housepower/spark-clickhouse-connector], and capability to scale SQL as a network service.

Disclosure: I work for ClickHouse

• spark-clickhouse-connector

  1 167 8.1 Scala

  Spark ClickHouse Connector build on DataSourceV2 API

  

Agree with the OP that SQL will almost assuredly still be in use for 20+ years in the future, given the simplicity and flexibility of the declarative language, standardization, and as applicable to today as it was then to our big data problems.

Any discussion of SQL at scale must include ClickHouse [https://clickhouse.com/docs/en/install#self-managed-install], given it's broad open-source use, integrations available for Spark with JDBC [https://github.com/ClickHouse/clickhouse-jdbc/] or the open-source Spark-ClickHouse Connector [https://github.com/housepower/spark-clickhouse-connector], and capability to scale SQL as a network service.

Disclosure: I work for ClickHouse

• prql

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  PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement

  

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