Update config docs

docs/source/user-guide/configs.md

@@ -76,7 +76,7 @@ Environment variables are read during `SessionConfig` initialisation so they mus
 | datafusion.execution.parquet.allow_single_file_parallelism              | true                      | (writing) Controls whether DataFusion will attempt to speed up writing parquet files by serializing them in parallel. Each column in each row group in each output file are serialized in parallel leveraging a maximum possible core count of n_files*n_row_groups*n_columns.                                                                                                                                                                                                                                                                                                                          |
 | datafusion.execution.parquet.maximum_parallel_row_group_writers         | 1                         | (writing) By default parallel parquet writer is tuned for minimum memory usage in a streaming execution plan. You may see a performance benefit when writing large parquet files by increasing maximum_parallel_row_group_writers and maximum_buffered_record_batches_per_stream if your system has idle cores and can tolerate additional memory usage. Boosting these values is likely worthwhile when writing out already in-memory data, such as from a cached data frame.                                                                                                                          |
 | datafusion.execution.parquet.maximum_buffered_record_batches_per_stream | 2                         | (writing) By default parallel parquet writer is tuned for minimum memory usage in a streaming execution plan. You may see a performance benefit when writing large parquet files by increasing maximum_parallel_row_group_writers and maximum_buffered_record_batches_per_stream if your system has idle cores and can tolerate additional memory usage. Boosting these values is likely worthwhile when writing out already in-memory data, such as from a cached data frame.                                                                                                                          |
-| datafusion.execution.parquet.schema_force_string_view                   | false                     | (reading) If true, parquet reader will read columns of `Utf8/Utf8Large` with `Utf8View`, and `Binary/BinaryLarge` with `BinaryView`.                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
+| datafusion.execution.parquet.schema_force_string_view                   | true                      | (reading) If true, parquet reader will read columns of `Utf8/Utf8Large` with `Utf8View`, and `Binary/BinaryLarge` with `BinaryView`.                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
 | datafusion.execution.aggregate.scalar_update_factor                     | 10                        | Specifies the threshold for using `ScalarValue`s to update accumulators during high-cardinality aggregations for each input batch. The aggregation is considered high-cardinality if the number of affected groups is greater than or equal to `batch_size / scalar_update_factor`. In such cases, `ScalarValue`s are utilized for updating accumulators, rather than the default batch-slice approach. This can lead to performance improvements. By adjusting the `scalar_update_factor`, you can balance the trade-off between more efficient accumulator updates and the number of groups affected. |
 | datafusion.execution.planning_concurrency                               | 0                         | Fan-out during initial physical planning. This is mostly use to plan `UNION` children in parallel. Defaults to the number of CPU cores on the system                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
 | datafusion.execution.sort_spill_reservation_bytes                       | 10485760                  | Specifies the reserved memory for each spillable sort operation to facilitate an in-memory merge. When a sort operation spills to disk, the in-memory data must be sorted and merged before being written to a file. This setting reserves a specific amount of memory for that in-memory sort/merge process. Note: This setting is irrelevant if the sort operation cannot spill (i.e., if there's no `DiskManager` configured).                                                                                                                                                                       |