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A new C++ vectorized database acceleration library aimed to optimizing query engines and data processing systems.

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Velox is a C++ database acceleration library which provides reusable, extensible, and high-performance data processing components. These components can be reused to build compute engines focused on different analytical workloads, including batch, interactive, stream processing, and AI/ML. Velox was created by Facebook and it is currently developed in partnership with Intel, ByteDance, and Ahana.

In common usage scenarios, Velox takes a fully optimized query plan as input and performs the described computation. Considering Velox does not provide a SQL parser, a dataframe layer, or a query optimizer, it is usually not meant to be used directly by end-users; rather, it is mostly used by developers integrating and optimizing their compute engines.

Velox provides the following high-level components:

  • Type: a generic typing system that supports scalar, complex, and nested types, such as structs, maps, arrays, tensors, etc.
  • Vector: an Arrow-compatible columnar memory layout module, which provides multiple encodings, such as Flat, Dictionary, Constant, Sequence/RLE, and Bias, in addition to a lazy materialization pattern and support for out-of-order writes.
  • Expression Eval: a fully vectorized expression evaluation engine that allows expressions to be efficiently executed on top of Vector/Arrow encoded data.
  • Function Packages: sets of vectorized function implementations following the Presto and Spark semantic.
  • Operators: implementation of common data processing operators such as scans, projection, filtering, groupBy, orderBy, shuffle, hash join, unnest, and more.
  • I/O: a generic connector interface that allows different file formats (ORC/DWRF and Parquet) and storage adapters (S3, HDFS, local files) to be used.
  • Network Serializers: an interface where different wire protocols can be implemented, used for network communication, supporting PrestoPage and Spark's UnsafeRow.
  • Resource Management: a collection of primitives for handling computational resources, such as memory arenas and buffer management, tasks, drivers, and thread pools for CPU and thread execution, spilling, and caching.

Velox is extensible and allows developers to define their own engine-specific specializations, including:

  1. Custom types
  2. Simple and vectorized functions
  3. Aggregate functions
  4. Operators
  5. File formats
  6. Storage adapters
  7. Network serializers

Examples

Examples of extensibility and integration with different component APIs can be found here

Documentation

Developer guides detailing many aspects of the library, in addition to the list of available functions can be found here.

Getting Started

We provide scripts to help developers setup and install Velox dependencies.

Setting up on macOS

See scripts/setup-macos.sh

Setting up on Linux (Ubuntu 20.04 or later)

See scripts/setup-ubuntu.sh

Building Velox

Run make in the root directory to compile the sources. For development, use make debug to build a non-optimized debug version, or make release to build an optimized version. Use make unittest to build and run tests.

Contributing

Check our contributing guide to learn about how to contribute to the project.

Community

The main communication channel with the Velox OSS community is through the the Velox-OSS Slack workspace. Please don't hesitate in reaching out.

License

Velox is licensed under the Apache 2.0 License. A copy of the license can be found here.

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A new C++ vectorized database acceleration library aimed to optimizing query engines and data processing systems.

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