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Fixup links in README.md
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README.md

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# Ballista: Distributed SQL Query Engine, built on Apache Arrow
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Ballista is a distributed SQL query engine powered by the Rust implementation of [Apache Arrow](arrow) and
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[DataFusion](datafusion).
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Ballista is a distributed SQL query engine powered by the Rust implementation of [Apache Arrow][arrow] and
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[DataFusion][datafusion].
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If you are looking for documentation for a released version of Ballista, please refer to the
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[Ballista User Guide](user-guide).
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[Ballista User Guide][user-guide].
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## Overview
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Apache Spark in some cases, which means that more processing can fit on a single node, reducing the overhead of
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distributed compute.
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- The use of Apache Arrow as the memory model and network protocol means that data can be exchanged efficiently between
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executors using the [Flight Protocol](flight), and between clients and schedulers/executors using the
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[Flight SQL Protocol](flight-sql)
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executors using the [Flight Protocol][flight], and between clients and schedulers/executors using the
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[Flight SQL Protocol][flight-sql]
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## Features
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- Supports HDFS as well as cloud object stores. S3 is supported today and GCS and Azure support is planned.
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- DataFrame and SQL APIs available from Python and Rust.
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- Clients can connect to a Ballista cluster using [Flight SQL](flight-sql).
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- Clients can connect to a Ballista cluster using [Flight SQL][flight-sql].
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- JDBC support via Arrow Flight SQL JDBC Driver
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- Scheduler web interface and REST UI for monitoring query progress and viewing query plans and metrics.
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- Support for Docker, Docker Compose, and Kubernetes deployment, as well as manual deployment on bare metal.
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## Architecture Overview
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There are currently no up-to-date architecture documents available. You can get a general overview of the architecture
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by watching the [Ballista: Distributed Compute with Rust and Apache Arrow](ballista-talk) talk from the New York Open
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by watching the [Ballista: Distributed Compute with Rust and Apache Arrow][ballista-talk] talk from the New York Open
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Statistical Programming Meetup (Feb 2021).
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## Contribution Guide

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