Presto
Apache Calcite
Presto | Apache Calcite | |
---|---|---|
14 | 28 | |
15,646 | 4,400 | |
0.8% | 1.8% | |
9.9 | 9.0 | |
1 day ago | 1 day ago | |
Java | Java | |
Apache License 2.0 | Apache License 2.0 |
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Presto
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Multi-Database Support in DuckDB
We have some of this functionality in Presto (https://github.com/prestodb/presto), but it takes fair bit of work to implement it for all the different backends.
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Rust std:fs slower than Python
Note that glibc has a similar problem in multithreaded contexts. It strands unused memory in thread-local pools, which grows your memory usage over time like a memory leak. We got lower memory usage that didn't grow over time by switching to jemalloc.
Example of this: https://github.com/prestodb/presto/issues/8993
- Ask HN: What are some SQL transpilers?
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Cheat sheet for quotes usage?
I look at the grammar. Here is preto's grammar which is mostly similar to other sql engines: https://github.com/prestodb/presto/blob/master/presto-parser/src/main/antlr4/com/facebook/presto/sql/parser/SqlBase.g4
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After a few recent events, opening a Linux terminal in public places is a big no-no
export MVNW_VERBOSE=true git clone https://github.com/prestodb/presto.git cd presto bash ./mvnw clean install
- presto: The official home of the Presto distributed SQL query engine for big data
- Compile the Minecraft Server (Java Edition) to Native with GraalVM Native Image
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What are y'all learning right now?
more specifically, recently started learning about Presto [paper], and have been diving deeper into [source] code.
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DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
Presto
- Let's write a compiler, part 5: A code generator
Apache Calcite
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Data diffs: Algorithms for explaining what changed in a dataset (2022)
> Make diff work on more than just SQLite.
Another way of doing this that I've been wanting to do for a while is to implement the DIFF operator in Apache Calcite[0]. Using Calcite, DIFF could be implemented as rewrite rules to generate the appropriate SQL to be directly executed against the database or the DIFF operator can be implemented outside of the database (which the original paper shows is more efficient).
[0] https://calcite.apache.org/
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Apache Baremaps: online maps toolkit
Yes, planetiler rocks and the memory mapped collections enabled us to remove our dependency to rocksdb.
From my perspective, planetiler started as an effort to generate vector tiles from the OpenMapTile schema as fast as possible (pbf -> mvt). By contrast, Baremaps started as an effort to create a new schema and style from the ground up. In this regard, having a database (pbf -> db <- mvt) enables to live reload changes made in the configuration files. The database has a cost, but also comes with additional advantages (updates, dynamic data, generation of tiles at zoom levels 16+, etc.).
That being said, I think the two projects overlap and I hope we will find opportunities to collaborate in the future. For instance, whereas PostgreSQL is still required in Baremaps, I recently ported a lot of the ST_ function of Postgis to Apache Calcite with the intent to execute SQL on fast memory mapped collection.
https://github.com/apache/calcite/blob/main/core/src/main/ja...
A planet wide import in Postgis currently takes about 4 hours with the COPY API (easy to parallelize) followed by about 12 hours of simplification in Postgis (not easy to parallelize). I will try to publish a detailed benchmark in the future.
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How to manipulate SQL string programmatically?
Use a SQL Parser like sqlglot or Apache Calcite to compile user's query into an AST.
- Can SQL be used without an RDBMS?
- Apache Calcite
- Want to contribute more to open source projects.
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CITIC Industrial Cloud — Apache ShardingSphere Enterprise Applications
The SQL Federation engine contains processes such as SQL Parser, SQL Binder, SQL Optimizer, Data Fetcher and Operator Calculator, suitable for dealing with co-related queries and subqueries cross multiple database instances. At the underlying layer, it uses Calcite to implement RBO (Rule Based Optimizer) and CBO (Cost Based Optimizer) based on relational algebra, and query the results through the optimal execution plan.
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Postgres wire compatible SQLite proxy
Awesome to see work in the DB wire compatible space. On the MySQL side, there was MySQL Proxy (https://github.com/mysql/mysql-proxy), which was scriptable with Lua, with which you could create your own MySQL wire compatible connections. Unfortunately it appears to have been abandoned by Oracle and IIRC doesn't work with 5.7 and beyond. I used it in the past to hack together a MySQL wire adapter for Interana (https://scuba.io/).
I guess these days the best approach for connecting arbitrary data sources to existing drivers, at least for OLAP, is Apache Calcite (https://calcite.apache.org/). Unfortunately that feels a little more involved.
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Launch HN: Hydra (YC W22) – Query Any Database via Postgres
For anyone interested, Apache Calcite[0] is an open source data management framework which seems to do many of the same things that Hydra claims to do, but taking a different approach. Operating as a Java library, Calcite contains "adapters" to many different data sources from existing JDBC connectors to Elasticsearch to Cassandra. All of these different data sources can be joined together as desired. Calcite also has it's own optimizer which is able to push down relevant parts of the query to the different data sources. However, you get full SQL on data sources which don't support it, with Calcite executing the remaining bits itself.
Unfortunately, I would not be too surprised if Calcite was found to be less performance-optimized than Hydra. That said, there are users of Calcite at Google, Uber, Spotify, and others who have made great use of various parts of the framework.
[0] https://calcite.apache.org/
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Anyone know of any software that can help in designing then outputting to various database
Abstraction Layer - You can use something like Calcite to abstract out your data storage. https://calcite.apache.org/
What are some alternatives?
Trino - Official repository of Trino, the distributed SQL query engine for big data, former
Apache Phoenix - Apache Phoenix
ANTLR - ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files.
HikariCP - 光 HikariCP・A solid, high-performance, JDBC connection pool at last.
JSqlParser - JSqlParser parses an SQL statement and translate it into a hierarchy of Java classes. The generated hierarchy can be navigated using the Visitor Pattern
jOOQ - jOOQ is the best way to write SQL in Java
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Spring Data JPA - Simplifies the development of creating a JPA-based data access layer.
Apache Drill - Apache Drill is a distributed MPP query layer for self describing data
zetasql - ZetaSQL - Analyzer Framework for SQL