Support lazy materialization of row groups in ParquetFileReader

Motivation: The current behavior of ParquetFilterReader#readNextRowGroup is to eagerly enumerate all chunks in the row group, then read all pages in the chunk. For distributed data workloads, this can cause significant memory pressure, particularly for use cases that require the colocation of multiple Parquet files on a single worker.

Proposal: A Parquet Configuration option that enables lazy row group reading, i.e., only a page at a time (plus whatever header is necessary to read that header). The Configuration option could be either a flag, or an int value for how many pages/page bytes to buffer at a time.

I think this could be accomplished by modifying [ParquetFileReader#readAllPages](https://github.com/apache/parquet-mr/blob/cf294a35ca4b635f44357fe4c170f3b66870dc6e/parquet-hadoop/src/main/java/org/apache/parquet/hadoop/ParquetFileReader.java#L1727) to re-implement pagesInChunk as an Iterator, rather than a List. Then, ColumnChunkPageReader could parse the Configuration option above and decide whether to fully materialize the iterator or not.

I'm happy to try to create a draft/branch for this to get some early feedback on the idea!

**Reporter**: [Claire McGinty](https://issues.apache.org/jira/secure/ViewProfile.jspa?name=clairemcginty) / @clairemcginty
#### PRs and other links:
- [GitHub Pull Request #1293](https://github.com/apache/parquet-mr/pull/1293)

_{**Note**: *This issue was originally created as [PARQUET-2443](https://issues.apache.org/jira/browse/PARQUET-2443). Please see the [migration documentation](https://issues.apache.org/jira/browse/PARQUET-2502) for further details.*}

Start with ParquetFileReader#readAllPages in parquet-hadoop and the ColumnChunkPageReader behavior described in the proposal; review Pull Request #1293 for existing work. Done means a Parquet configuration option supports lazy row-group page materialization while preserving the existing eager behavior when disabled.

Written by the indexing model from the issue text.