Apache Calcite
Apache Hive
Apache Calcite | Apache Hive | |
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28 | 14 | |
4,376 | 5,341 | |
1.3% | 0.8% | |
9.0 | 9.6 | |
1 day ago | 1 day ago | |
Java | Java | |
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.
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/
Apache Hive
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Apache Iceberg as storage for on-premise data store (cluster)
Trino or Hive for SQL querying. Get Trino/Hive to talk to Nessie.
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In One Minute : Hadoop
Hive, A data warehouse infrastructure that provides data summarization and ad hoc querying.
- Visionary French entrepreneur, David Gurle, launches new venture – Hive
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DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
Apache Drill, Druid, Flink, Hive, Kafka, Spark
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Apache Spark, Hive, and Spring Boot — Testing Guide
In this article, I'm showing you how to create a Spring Boot app that loads data from Apache Hive via Apache Spark to the Aerospike Database. More than that, I'm giving you a recipe for writing integration tests for such scenarios that can be run either locally or during the CI pipeline execution. The code examples are taken from this repository.
- Apache Hive in the vein!
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Jinja2 not formatting my text correctly. Any advice?
ListItem(name='Apache Hive', website='https://hive.apache.org/', category='Interactive Query', short_description='Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data query and analysis. Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.'),
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Understanding SQL Dialects
Apache Hive takes in a specific SQL dialect and converts it to map-reduce.
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The Data Engineer Roadmap 🗺
Apache Hive
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Open Source SQL Parsers
Apache Calcite is a popular parser/optimizer that is used in popular databases and query engines like Apache Hive, BlazingSQL and many others.
What are some alternatives?
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
superset - Apache Superset is a Data Visualization and Data Exploration Platform
ANTLR - ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files.
ObjectBox Java (Kotlin, Android) - Java and Android Database - fast and lightweight without any ORM
Presto - The official home of the Presto distributed SQL query engine for big data
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
Apache Phoenix - Apache Phoenix
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Flyway - Flyway by Redgate • Database Migrations Made Easy.
Apache Drill - Apache Drill is a distributed MPP query layer for self describing data