sqlfluff
delta
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sqlfluff | delta | |
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35 | 69 | |
7,199 | 6,897 | |
2.1% | 2.2% | |
9.6 | 9.8 | |
5 days ago | about 5 hours ago | |
Python | Scala | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sqlfluff
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🐍🐍 23 issues to grow yourself as an exceptional open-source Python expert 🧑💻 🥇
Repo : https://github.com/sqlfluff/sqlfluff
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SQL Reserved Words – The Empirical List
I'm surprised sqlfluff hasn't been mentioned yet. Perhaps not a comprehensive list, but it's worked for everything I've thrown at it. There's an ANSI keyword list [0], and then dialect-specific lists for everything from DB2 [1] to Snowflake [2].
[0]: https://github.com/sqlfluff/sqlfluff/blob/main/src/sqlfluff/...
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Show HN: Postgres Language Server
It has tons of annoying quirks, but I couldn't imagine running a DBT project without it: https://github.com/sqlfluff/sqlfluff
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Front page news headline scraping data engineering project
Move SQL queries to sql files and read from files (Use sqlfluff to lint the code https://github.com/sqlfluff/sqlfluff)
- Anything like SQLFluff written in Rust?
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Code autoformatter for SQL in VSCode that plays nicely with dbt
SQLFluff is a good CLI tool for this and includes support for jinja and dbt. I don't think there's a VSCode plugin for it yet.
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Ask HN: How do you test SQL?
This linter can really enforce some best practices https://github.com/sqlfluff/sqlfluff
A list of best practices:
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What is something you would learn at college but not a bootcamp (hard skills)
BigQuery SQL and SQLFluff
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Is the knowledge on how Compilers work applicable to the role of a Data Engineer?
There's a SQL parser/linter called SQLFluff that my team uses for our CI/CD. I've made a few pull requests to fix the parser for the particular SQL dialect we used, and my college compiler classes definitely helped.
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sqlfluff VS ANTLR - a user suggested alternative
2 projects | 12 Dec 2022
delta
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Delta Lake vs. Parquet: A Comparison
Delta is pretty great, let's you do upserts into tables in DataBricks much easier than without it.
I think the website is here: https://delta.io
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Understanding Parquet, Iceberg and Data Lakehouses
I often hear references to Apache Iceberg and Delta Lake as if they’re two peas in the Open Table Formats pod. Yet…
Here’s the Apache Iceberg table format specification:
https://iceberg.apache.org/spec/
As they like to say in patent law, anyone “skilled in the art” of database systems could use this to build and query Iceberg tables without too much difficulty.
This is nominally the Delta Lake equivalent:
https://github.com/delta-io/delta/blob/master/PROTOCOL.md
I defy anyone to even scope out what level of effort would be required to fully implement the current spec, let alone what would be involved in keeping up to date as this beast evolves.
Frankly, the Delta Lake spec reads like a reverse engineering of whatever implementation tradeoffs Databricks is making as they race to build out a lakehouse for every Fortune 1000 company burned by Hadoop (which is to say, most of them).
My point is that I’ve yet to be convinced that buying into Delta Lake is actually buying into an open ecosystem. Would appreciate any reassurance on this front!
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Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog
Apache Iceberg is one of the three types of lakehouse, the other two are Apache Hudi and Delta Lake.
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[D] Is there other better data format for LLM to generate structured data?
The Apache Spark / Databricks community prefers Apache parquet or Linux Fundation's delta.io over json.
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Delta vs Iceberg: make love not war
Delta 3.0 extends an olive branch. https://github.com/delta-io/delta/releases/tag/v3.0.0rc1
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Databricks Strikes $1.3B Deal for Generative AI Startup MosaicML
Databricks provides Jupyter lab like notebooks for analysis and ETL pipelines using spark through pyspark, sparkql or scala. I think R is supported as well but it doesn't interop as well with their newer features as well as python and SQL do. It interfaces with cloud storage backend like S3 and offers some improvements to the parquet format of data querying that allows for updating, ordering and merged through https://delta.io . They integrate pretty seamlessly to other data visualisation tooling if you want to use it for that but their built in graphs are fine for most cases. They also have ML on rails type through menus and models if I recall but I typically don't use it for that. I've typically used it for ETL or ELT type workflows for data that's too big or isn't stored in a database.
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The "Big Three's" Data Storage Offerings
Structured, Semi-structured and Unstructured can be stored in one single format, a lakehouse storage format like Delta, Iceberg or Hudi (assuming those don't require low-latency SLAs like subsecond).
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Ideas/Suggestions around setting up a data pipeline from scratch
As the data source, what I have is a gRPC stream. I get data in protobuf encoded format from it. This is a fixed part in the overall system, there is no other way to extract the data. We plan to ingest this data in delta lake, but before we do that there are a few problems.
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Medallion/lakehouse architecture data modelling
Take a look at Delta Lake https://delta.io, it enables a lot of database-like actions on files
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CSV or Parquet File Format
I prefer parquet (or delta for larger datasets. CSV for very small datasets, or the ones that will be later used/edited in Excel or Googke sheets.
What are some alternatives?
vscode-sqlfluff - An extension to use the sqlfluff linter in vscode.
dvc - 🦉 ML Experiments and Data Management with Git
sqlparse - A non-validating SQL parser module for Python
Apache Cassandra - Mirror of Apache Cassandra
dbt-utils - Utility functions for dbt projects.
lakeFS - lakeFS - Data version control for your data lake | Git for data
ale - Check syntax in Vim/Neovim asynchronously and fix files, with Language Server Protocol (LSP) support
hudi - Upserts, Deletes And Incremental Processing on Big Data.
soda-sql - Data profiling, testing, and monitoring for SQL accessible data.
delta-rs - A native Rust library for Delta Lake, with bindings into Python
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
iceberg - Apache Iceberg