pev2
octosql
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pev2 | octosql | |
---|---|---|
40 | 34 | |
2,363 | 4,695 | |
3.4% | - | |
7.7 | 1.2 | |
11 days ago | 4 days ago | |
TypeScript | Go | |
PostgreSQL License | Mozilla Public 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.
pev2
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Retrieving the latest row per group from PostgreSQL
This runs in about 250ms. Let's have a look at the explain plan to understand it better. To visualise it, I am using the excellent visualisation tool from Dalibo.
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Pg_hint_plan: Force PostgreSQL to execute query plans how you want
The PEV2 is open source and give you a good visualization. I never used this pgmustard to compare.
https://explain.dalibo.com/
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Efficient Database Queries in Rails: A Practical Approach
Visualize Your Plan: Visit explain.dalibo.com and paste the generated plan text and query. Then, hit Submit. The tool will generate a visualization of your query plan. Here's an example of the visualization for the fifth attempt version of the query from this post. It shows the different types of scans that were used and how the data gets combined. The duration of each operation is also shown:
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What's new in the Postgres 16 query planner (a.k.a. optimizer)
You can download the whole analyzer as a simple html file and use it this way. No need to obfuscate or sanitize anything at all.
https://github.com/dalibo/pev2
- Visualizing and understanding PostgreSQL EXPLAIN plans made easy
- Don't use DISTINCT as a "join-fixer"
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When should you use the IN instead of the OR operator in Postgres queries?
You might be interested in sites like https://explain.dalibo.com/ which make the output a bit nicer to read. I use these quite often to quickly identify bottlenecks.
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200 Web-Based, Must-Try Web Design and Development Tools
PostgreSQL Query Plan Analyzer and Visualizer
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Do you use pgAdmin? Why?
I didn’t know about pev2, interesting, checking it now. Did you integrate the component yourself or are you using this hosted page by them: https://explain.dalibo.com/?
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Tuning DB
IMO it‘s important to get started with indexing. Grab your most frequently used queries and run an EXPLAIN ANALYZE to identify the problems. This tool might help you to understand your execution plans. Once you identified your problems, you can build indexes and check again. Then you should regularly check if your indexes are used.
octosql
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Wazero: Zero dependency WebAssembly runtime written in Go
Never got it to anything close to a finished state, instead moving on to doing the same prototype in llvm and then cranelift.
That said, here's some of the wazero-based code on a branch - https://github.com/cube2222/octosql/tree/wasm-experiment/was...
It really is just a very very basic prototype.
- Analyzing multi-gigabyte JSON files locally
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DuckDB: Querying JSON files as if they were tables
This is really cool!
With their Postgres scanner[0] you can now easily query multiple datasources using SQL and join between them (i.e. Postgres table with JSON file). Something I strived to build with OctoSQL[1] before.
It's amazing to see how quickly DuckDB is adding new features.
Not a huge fan of C++, which is right now used for authoring extensions, it'd be really cool if somebody implemented a Rust extension SDK, or even something like Steampipe[2] does for Postgres FDWs which would provide a shim for quickly implementing non-performance-sensitive extensions for various things.
Godspeed!
[0]: https://duckdb.org/2022/09/30/postgres-scanner.html
[1]: https://github.com/cube2222/octosql
[2]: https://steampipe.io
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Show HN: ClickHouse-local – a small tool for serverless data analytics
Congrats on the Show HN!
It's great to see more tools in this area (querying data from various sources in-place) and the Lambda use case is a really cool idea!
I've recently done a bunch of benchmarking, including ClickHouse Local and the usage was straightforward, with everything working as it's supposed to.
Just to comment on the performance area though, one area I think ClickHouse could still possibly improve on - vs OctoSQL[0] at least - is that it seems like the JSON datasource is slower, especially if only a small part of the JSON objects is used. If only a single field of many is used, OctoSQL lazily parses only that field, and skips the others, which yields non-trivial performance gains on big JSON files with small queries.
Basically, for a query like `SELECT COUNT(*), AVG(overall) FROM books.json` with the Amazon Review Dataset, OctoSQL is twice as fast (3s vs 6s). That's a minor thing though (OctoSQL will slow down for more complicated queries, while for ClickHouse decoding the input is and remains the bottleneck).
[0]: https://github.com/cube2222/octosql
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Steampipe – Select * from Cloud;
To add somewhat of a counterpoint to the other response, I've tried the Steampipe CSV plugin and got 50x slower performance vs OctoSQL[0], which is itself 5x slower than something like DataFusion[1]. The CSV plugin doesn't contact any external API's so it should be a good benchmark of the plugin architecture, though it might just not be optimized yet.
That said, I don't imagine this ever being a bottleneck for the main use case of Steampipe - in that case I think the APIs themselves will always be the limiting part. But it does - potentially - speak to what you can expect if you'd like to extend your usage of Steampipe to more than just DevOps data.
[0]: https://github.com/cube2222/octosql
[1]: https://github.com/apache/arrow-datafusion
Disclaimer: author of OctoSQL
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Go runtime: 4 years later
Actually, folks just use gRPC or Yaegi in Go.
See Terraform[0], Traefik[1], or OctoSQL[2].
Although I agree plugins would be welcome, especially for performance reasons, though also to be able to compile and load go code into a running go process (JIT-ish).
[0]: https://github.com/hashicorp/terraform
[1]: https://github.com/traefik/traefik
[2]: https://github.com/cube2222/octosql
Disclaimer: author of OctoSQL
- Run SQL on CSV, Parquet, JSON, Arrow, Unix Pipes and Google Sheet
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Beginner interested in learning SQL. Have a few question that I wasn’t able to find on google.
Through more magic, you COULD of course use stuff like Spark, or easier with programs like TextQL, sq, OctoSQL.
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How I Used DALL·E 2 to Generate The Logo for OctoSQL
The logo was created for OctoSQL and in the article you can find a lot of sample phrase-image combinations, as it describes the whole path (generation, variation, editing) I went down. Let me know what you think!
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How I Used DALL·E 2 to Generate the Logo for OctoSQL
Hey, author here, happy to answer any questions!
The logo was created for OctoSQL[0] and in the article you can find a lot of sample phrase-image combinations, as it describes the whole path (generation, variation, editing) I went down. Let me know what you think!
[0]:https://github.com/cube2222/octosql
What are some alternatives?
TypeORM - ORM for TypeScript and JavaScript. Supports MySQL, PostgreSQL, MariaDB, SQLite, MS SQL Server, Oracle, SAP Hana, WebSQL databases. Works in NodeJS, Browser, Ionic, Cordova and Electron platforms.
duckdb - DuckDB is an in-process SQL OLAP Database Management System
awesome-db-tools - Everything that makes working with databases easier
q - q - Run SQL directly on delimited files and multi-file sqlite databases
hypopg - Hypothetical Indexes for PostgreSQL
trdsql - CLI tool that can execute SQL queries on CSV, LTSV, JSON, YAML and TBLN. Can output to various formats.
pev - Postgres Explain Visualizer
sqlitebrowser - Official home of the DB Browser for SQLite (DB4S) project. Previously known as "SQLite Database Browser" and "Database Browser for SQLite". Website at:
sysbench - Scriptable database and system performance benchmark
sqlite-utils - Python CLI utility and library for manipulating SQLite databases
yugabyte-db - YugabyteDB - the cloud native distributed SQL database for mission-critical applications.
textql - Execute SQL against structured text like CSV or TSV