docs/source/user-guide/quickstart.md

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# Quickstart

This page walks through a complete query end-to-end.

## The full example

```java
import org.apache.arrow.memory.RootAllocator;
import org.apache.arrow.vector.ipc.ArrowReader;
import org.apache.datafusion.DataFrame;
import org.apache.datafusion.SessionContext;

try (var allocator = new RootAllocator();
     var ctx = new SessionContext()) {

    ctx.registerParquet("orders", "/path/to/orders.parquet");

    try (DataFrame df = ctx.sql(
            "SELECT o_orderpriority, COUNT(*) AS n " +
            "FROM orders GROUP BY o_orderpriority");
         ArrowReader reader = df.collect(allocator)) {
        while (reader.loadNextBatch()) {
            var batch = reader.getVectorSchemaRoot();
            // ...
        }
    }
}
```

## Walkthrough

**Allocator.** `RootAllocator` is the Arrow off-heap memory allocator. Every
JVM-side Arrow buffer is tracked under an allocator; when the allocator is
closed, leaked buffers are reported. Use one allocator per query (or one
per application) and close it in a `try`-with-resources.

**Session context.** `SessionContext` is the entry point into DataFusion. It
holds the catalog of registered tables and the query planner. It is
`AutoCloseable` and **not thread-safe** — use one per thread, or guard
access externally.

**Registering data.** `registerParquet(name, path)` reads the file's footer
on call and exposes it under the given table name. See
[Parquet](parquet.md) for the options form.

**SQL.** `ctx.sql("...")` plans the query and returns a `DataFrame`. The
query is not executed until results are pulled.

**Collecting results.** `df.collect(allocator)` starts native execution and
returns an `ArrowReader`. Each `loadNextBatch()` call pulls the next
`VectorSchemaRoot`; iterate until it returns `false`.

**Cleanup.** Both `SessionContext` and `DataFrame` are `AutoCloseable`. Use
`try`-with-resources so native resources and Arrow buffers are released
even on exception.