Off heap memory leaks with large binary fields using Snappy

When I write a large pages (~100MB) that contains large binary fields (~1MB), the java application uses an unexpected amount of off-heap memory (1.2GB)

This problem was identified when using the `AvroParquetWriter` but its source lies in the parquet-hadoop submodule.

Diving a little bit deeper shows the following:
- writing fields into the ParquetWriter creates a SequenceBytesIn which is actually just a list of `BytesInput` for each field. When calling `bytes.writeAllTo(cos)` in the `CodecFactory`, it actually writes one `ByteInput` (which contains a single field) at a time.
- the `SnappyCompressor` receives the data in `setInput` one large field at a time. This calls `ByteBuffer.allocateDirect` each time with a growing size. But as the memory is actually allocated off-heap, this does not trigger the garbage collector which only sees small objects on the heap. The actual memory associated with the object is the size of all the fields added to the page until then, so off-heap the memory is growing quadratically.

I did not attach a pull request to this issue because I see multiple mitigation to the issue but I'm not really delighted by any of them:
- merge all the fields into one byte array before pushing them down to the `SnappyCompressor`. For instance we could replace the previous statement in the `CodecFactory` with `BytesInput.from(bytes.toByteArray()).writeAllTo(cos)`. But this generates an extra on-heap allocation the size of the whole page.
- force the `DirectBuffer` to be cleaned up with something like `((DirectBuffer)inputBuffer).cleaner().clean()` after having copied it to the new bigger buffer. The issue here would be that `DirectBuffer` is part of the internal API and is likely to be moved. Using reflexion could make the solution more resilient but is even "hackier" IMHO.

**Reporter**: [Remi Dettai](https://issues.apache.org/jira/secure/ViewProfile.jspa?name=remi.dettai)

_{**Note**: *This issue was originally created as [PARQUET-1188](https://issues.apache.org/jira/browse/PARQUET-1188). Please see the [migration documentation](https://issues.apache.org/jira/browse/PARQUET-2502) for further details.*}

从 parquet-hadoop 子模块开始，跟踪 ParquetWriter 和 SequenceBytesIn 到 CodecFactory 和 SnappyCompressor。使用包含 1MB 二进制字段、大小约为 100MB 的页面重现该问题，然后评估提出的缓解路径。完成的标准是：大规模写入不再导致 off-heap 内存呈二次增长，同时保持 writer 的行为不变。

由索引模型根据 Issue 内容生成。