Quill
deequ
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Quill | deequ | |
---|---|---|
15 | 17 | |
2,136 | 3,119 | |
0.0% | 1.3% | |
9.1 | 7.5 | |
2 days ago | about 23 hours ago | |
Scala | Scala | |
Apache License 2.0 | 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.
Quill
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Dear Sir, You Have Built a Compiler (2022)
https://github.com/zio/zio-quill
This library does exactly what you prescribe. Pretty sure under the hood it's using macros with string templates
- Sketch of a Post-ORM
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Why use Spark?
But I can connect to Postgress with something like Quill and run sophisticated queries to fetch data. Which then got me thinking, what is the difference between using Spark to connect to the database and using something like Quill or your normal pure JDBC driver?
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What's the point of opaque type aliases (and are they actually sound)?
Just as an example, say you are using quill ( https://getquill.io/ ) to query your database.
- I want to move to Scala 3, but I'm not sure what libraries to use
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Query DSL in Scala ?
I think Quill is the closest to your request: https://github.com/zio/zio-quill
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Doobie tutorial: databases and pure FP in Scala
If this still looks like too much hassle, you can always go a bit higher-level and use something like Quill, which is also a powerful approach that uses a different, more ORM-like style.
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Ask HN: What cutting-edge technology do you use?
I'm using it mostly for full-stack web development with ScalaJS (https://www.scala-js.org) in the frontend (https://outwatch.github.io/docs/readme.html) and in the backend with AWS lambdas.
The ecosystem is currently in the process of porting all the libraries to Scala 3. So if you're new to Scala, I'd recommend to start with Scala 2, which is rock-solid and already very powerful.
I never worked with SQLAlchemy. But on the scala database side, popular libraries are Doobie (https://tpolecat.github.io/doobie) and Quill (https://getquill.io). Keep in mind that these are for Scala on the JVM. On the ScalaJS side I'm using the javascript library pg. But I'd like to try if it works well with Prisma soon.
The nice thing about ScalaJS is, that you can use Javascript libraries. And if there are typescript facades, then you can transpile these to Scala and use them in a type safe way (https://scalablytyped.org).
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Fp libraries that target scala 3 exclusively?
I know that libraries like Scodec and shapeless were rewritten practically from scratch for Scala 3, taking advantage of the next syntax and internals, as well as protoquill - a Scala 3 implementation of Quill.
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Best Scala framework / libraries out there ?
Akka HTTP, Cats, Quill, ninny, Monix Observable, mill.
deequ
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[Data Quality] Deequ Feedback request
There's no straightforward way to drop and rerun a metric collection. For example, say you detect a problem in your data. You fix it, rerun the pipeline, and replace the bad data with the good. You'd want your metrics history to reflect the true state of your data. But the "bad run" cannot be dropped. Issue
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Thoughts on a business rules engine
I had similar requirements for QA reporting on large and diverse data sets. I implemented data check pipelines, with rules in AWS Deequ (https://github.com/awslabs/deequ) running on an Apache Spark cluster. The Deequ worked well for me, but there were a few cases where I opted to write the rule checks in the data store to improve throughput (i.e. SQL checks on critical data elements on the database).
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Building a data quality solution for devs and business people
Hey all! At the companies where I've worked as a developer, I've found that business stakeholders typically want a concrete way to check and assure the quality of data that pipelines are producing, before other downstream systems and users get impacted. I've tested solutions like Deequ, but I found that it made building compliance and data rules a bit more complicated and put a greater emphasis on developers to get the rules right that business was expecting. I also experienced issues with running checks in parallel and getting row level details about the failures.
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deequ VS cuallee - a user suggested alternative
2 projects | 30 Nov 2022
- November 15-19, 2022 FLiP Stack Weekly
- What are your favourite GitHub repos that shows how data engineering should be done?
- Well designed scala/spark project
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Soda Core (OSS) is now GA! So, why should you add checks to your data pipelines?
GE is arguably the most well known OSS alternative to Soda Core. The third option is deequ, originally developed and released in OSS by AWS. Our community has told us that Soda Core is different because itโs easy to get going and embed into data pipelines. And it also allows some of the check authoring work to be moved to other members of the data team. I'm sure there are also scenarios where Soda Core is not the best option. For example, when you only use Pandas dataframes or develop in Scala.
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Congrats on hitting the v1 milestone, whylabs! You're r/MLOps OSS tool of the month!
I wonder how this compares with tools like DeeQu (https://github.com/awslabs/python-deequ - requires Spark) or Pandas Profiling? One plus side I can see is that it doesn't require Apache Spark to run profiling (though a quick look at the code indicates that they are working on Spark support) and can work with real time systems.
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What companies/startups are using Scala (open source projects on github)?
There are so many of them in big data, e.g. Kafka, Spark, Flink, Delta, Snowplow, Finagle, Deequ, CMAK, OpenWhisk, Snowflake, TheHive, TVM-VTA, etc.
What are some alternatives?
Slick - Slick (Scala Language Integrated Connection Kit) is a modern database query and access library for Scala
soda-sql - Data profiling, testing, and monitoring for SQL accessible data.
doobie - Functional JDBC layer for Scala.
azure-kusto-spark - Apache Spark Connector for Azure Kusto
ScalikeJDBC - A tidy SQL-based DB access library for Scala developers. This library naturally wraps JDBC APIs and provides you easy-to-use APIs.
dbt-data-reliability - dbt package that is part of Elementary, the dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features.
Phantom - Schema safe, type-safe, reactive Scala driver for Cassandra/Datastax Enterprise
BigDL - Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max). A PyTorch LLM library that seamlessly integrates with llama.cpp, HuggingFace, LangChain, LlamaIndex, DeepSpeed, vLLM, FastChat, ModelScope, etc.
Clickhouse-scala-client - Clickhouse Scala Client with Reactive Streams support
re_data - re_data - fix data issues before your users & CEO would discover them ๐
zio-protoquill - Quill for Scala 3
SynapseML - Simple and Distributed Machine Learning