Awesome
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Ballista is a distributed execution engine which makes Apache DataFusion applications distributed.
Existing DataFusion application:
use datafusion::prelude::*;
#[tokio::main]
async fn main() -> datafusion::error::Result<()> {
let ctx = SessionContext::new();
// register the table
ctx.register_csv("example", "tests/data/example.csv", CsvReadOptions::new()).await?;
// create a plan to run a SQL query
let df = ctx.sql("SELECT a, MIN(b) FROM example WHERE a <= b GROUP BY a LIMIT 100").await?;
// execute and print results
df.show().await?;
Ok(())
}
can be distributed with few lines of code changed:
[!IMPORTANT]
There is a gap between DataFusion and Ballista, which may bring incompatibilities. The community is working hard to close this gap
use ballista::prelude::*;
use datafusion::prelude::*;
#[tokio::main]
async fn main() -> datafusion::error::Result<()> {
// create DataFusion SessionContext with ballista standalone cluster started
let ctx = SessionContext::standalone();
// register the table
ctx.register_csv("example", "tests/data/example.csv", CsvReadOptions::new()).await?;
// create a plan to run a SQL query
let df = ctx.sql("SELECT a, MIN(b) FROM example WHERE a <= b GROUP BY a LIMIT 100").await?;
// execute and print results
df.show().await?;
Ok(())
}
If you are looking for documentation or more examples, please refer to the Ballista User Guide.
Architecture
A Ballista cluster consists of one or more scheduler processes and one or more executor processes. These processes can be run as native binaries and are also available as Docker Images, which can be easily deployed with Docker Compose or Kubernetes.
The following diagram shows the interaction between clients and the scheduler for submitting jobs, and the interaction between the executor(s) and the scheduler for fetching tasks and reporting task status.
See the architecture guide for more details.
Performance
We run some simple benchmarks comparing Ballista with Apache Spark to track progress with performance optimizations. These are benchmarks derived from TPC-H and not official TPC-H benchmarks. These results are from running individual queries at scale factor 100 (100 GB) on a single node with a single executor and 8 concurrent tasks.
Overall Speedup
The overall speedup is 2.9x
Per Query Comparison
Relative Speedup
Absolute Speedup
Getting Started
The easiest way to get started is to run one of the standalone or distributed examples. After that, refer to the Getting Started Guide.
Project Status
Ballista supports a wide range of SQL, including CTEs, Joins, and subqueries and can execute complex queries at scale, but still there is a gap between DataFusion and Ballista which we want to bridge in near future.
Refer to the DataFusion SQL Reference for more information on supported SQL.
Contribution Guide
Please see the Contribution Guide for information about contributing to Ballista.