### What changes were proposed in this pull request?
1. Add the following parquet files to the resource folder `external/avro/src/test/resources`:
- Files saved by Spark 2.4.5 (cee4ecbb16) without meta info `org.apache.spark.version`
- `before_1582_date_v2_4_5.avro` with a date column: `avro.schema {"type":"record","name":"topLevelRecord","fields":[{"name":"dt","type":[{"type":"int","logicalType":"date"},"null"]}]}`
- `before_1582_timestamp_millis_v2_4_5.avro` with a timestamp column: `avro.schema {"type":"record","name":"test","namespace":"logical","fields":[{"name":"dt","type":["null",{"type":"long","logicalType":"timestamp-millis"}],"default":null}]}`
- `before_1582_timestamp_micros_v2_4_5.avro` with a timestamp column: `avro.schema {"type":"record","name":"topLevelRecord","fields":[{"name":"dt","type":[{"type":"long","logicalType":"timestamp-micros"},"null"]}]}`
- Files saved by Spark 2.4.6-rc3 (570848da7c) with the meta info `org.apache.spark.version 2.4.6`:
- `before_1582_date_v2_4_6.avro` is similar to `before_1582_date_v2_4_5.avro` except Spark version in parquet meta info.
- `before_1582_timestamp_micros_v2_4_6.avro` is similar to `before_1582_timestamp_micros_v2_4_5.avro` except meta info.
- `before_1582_timestamp_millis_v2_4_6.avro` is similar to `before_1582_timestamp_millis_v2_4_5.avro` except meta info.
2. Removed a few avro files becaused they are replaced by Avro files generated by Spark 2.4.5 above.
3. Add new test "generate test files for checking compatibility with Spark 2.4" to `AvroSuite` (marked as ignored). The parquet files above were generated by this test.
4. Modified "SPARK-31159: compatibility with Spark 2.4 in reading dates/timestamps" in `AvroSuite` to use new parquet files.
### Why are the changes needed?
To improve test coverage.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By `AvroV1Suite` and `AvroV2Suite`.
Closes#28664 from MaxGekk/avro-update-resource-files.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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