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# Java table providers

`SessionContext.registerTable(name, provider)` registers a Java-implemented
table. SQL queries that reference `name` call back into your `TableProvider`
to fetch batches. Data flows from Java to native code via the Arrow C Data
Interface, so there are no extra copies in the hot path. This is the Java
counterpart to DataFusion's Rust `SessionContext::register_table`.

## Implement

```java
import org.apache.arrow.memory.BufferAllocator;
import org.apache.arrow.vector.ipc.ArrowReader;
import org.apache.arrow.vector.types.pojo.Schema;
import org.apache.datafusion.TableProvider;

public final class MyTable implements TableProvider {
    private final Schema schema;

    public MyTable(Schema schema) {
        this.schema = schema;
    }

    @Override public Schema schema() { return schema; }

    @Override
    public ArrowReader scan(BufferAllocator allocator) {
        // Return a fresh ArrowReader. The reader must allocate its buffers
        // from `allocator` (or a child of it) — the framework needs the
        // allocator hierarchy to share a root.
        return openMyReader(allocator);
    }
}
```

For the common case of "I have a schema and a function that returns an
`ArrowReader`," `SimpleTableProvider` packages those two into a ready-made
`TableProvider` without having to subclass:

```java
TableProvider t = new SimpleTableProvider(mySchema(), allocator -> openMyReader(allocator));
ctx.registerTable("t", t);
```

## Register and query

```java
try (SessionContext ctx = new SessionContext();
     BufferAllocator allocator = new RootAllocator()) {
    ctx.registerTable("t", new MyTable(mySchema()));

    try (DataFrame df = ctx.sql("SELECT * FROM t WHERE x > 10");
         ArrowReader r = df.collect(allocator)) {
        while (r.loadNextBatch()) {
            // ...
        }
    }
}
```

## Contract

- `schema()` is called exactly once, on the caller's thread, at registration
  time. Throwing from it aborts registration with the original exception.
- `scan(allocator)` is called once per SQL query that touches the table, on a
  worker thread. It must return a fresh, independent `ArrowReader` on every
  call — this is what makes self-joins and `UNION ALL` over the same table
  work.
- The reader returned by `scan` must allocate its buffers from the supplied
  `allocator` (or a child of it). Arrow Java's `Data.exportArrayStream`
  requires the reader's allocator and the export allocator to share a root.
- The returned reader's schema must equal the schema returned by `schema()`.
  A mismatch fails the query.
- You do not need to close the returned reader yourself. The framework
  installs a release callback that closes it when the underlying FFI stream
  is dropped.

## Errors

Exceptions thrown from `scan()` or from the returned reader surface in the
`RuntimeException` raised by `collect()`. The error message includes the Java
exception class and `getMessage()`, in the same format used for scalar UDF
errors.

## Threading

`SessionContext` is single-threaded, but `scan(allocator)` may be invoked from
any DataFusion worker thread. If your implementation maintains mutable state
across scans, synchronise it.

## Limitations (v1)

- Single-partition scans only. DataFusion sees the table as one partition;
  multi-partition parallelism is a follow-up.
- No projection or filter pushdown. DataFusion applies projection and
  filters on top of the batches you return; the Java side always sees the
  full schema. The interface is intentionally minimal so it can grow these
  capabilities (as default methods) without breaking existing implementations.
- No `deregisterTable`. Tables live until the `SessionContext` is closed.