| `profiling.enabled` | | `False` | Whether profiling should be done. |
| `profiling.bigquery_temp_table_schema` | | | On bigquery for profiling partitioned tables needs to create temporary views. You have to define a schema where these will be created. Views will be cleaned up after profiler runs. (Great expectation tech details about this [here](https://legacy.docs.greatexpectations.io/en/0.9.0/reference/integrations/bigquery.html#custom-queries-with-sql-datasource). |
| `profiling.limit` | | | Max number of documents to profile. By default, profiles all documents. |
| `profiling.offset` | | | Offset in documents to profile. By default, uses no offset. |
| `profiling.max_workers` | | `5 * os.cpu_count()` | Number of worker threads to use for profiling. Set to 1 to disable. |
| `profiling.query_combiner_enabled` | | `True` | *This feature is still experimental and can be disabled if it causes issues.* Reduces the total number of queries issued and speeds up profiling by dynamically combining SQL queries where possible. |
| `profile_pattern.allow` | | `*` | List of regex patterns for tables or table columns to profile. Defaults to all. |
| `profile_pattern.deny` | | | List of regex patterns for tables or table columns to not profile. Defaults to none. |
| `profile_pattern.ignoreCase` | | `True` | Whether to ignore case sensitivity during pattern matching. |
| `profiling.turn_off_expensive_profiling_metrics` | | False | Whether to turn off expensive profiling or not. This turns off profiling for quantiles, distinct_value_frequencies, histogram & sample_values. This also limits maximum number of fields being profiled to 10. |
| `profiling.max_number_of_fields_to_profile` | | `None` | A positive integer that specifies the maximum number of columns to profile for any table. `None` implies all columns. The cost of profiling goes up significantly as the number of columns to profile goes up. |
| `profiling.profile_table_level_only` | | False | Whether to perform profiling at table-level only, or include column-level profiling as well. |
| `profiling.include_field_null_count` | | `True` | Whether to profile for the number of nulls for each column. |
| `profiling.include_field_min_value` | | `True` | Whether to profile for the min value of numeric columns. |
| `profiling.include_field_max_value` | | `True` | Whether to profile for the max value of numeric columns. |
| `profiling.include_field_mean_value` | | `True` | Whether to profile for the mean value of numeric columns. |
| `profiling.include_field_median_value` | | `True` | Whether to profile for the median value of numeric columns. |
| `profiling.include_field_stddev_value` | | `True` | Whether to profile for the standard deviation of numeric columns. |
| `profiling.include_field_quantiles` | | `False` | Whether to profile for the quantiles of numeric columns. |
| `profiling.include_field_histogram` | | `False` | Whether to profile for the histogram for numeric fields. |
| `profiling.include_field_sample_values` | | `True` | Whether to profile for the sample values for all columns. |
| `profiling.partition_datetime` | | | For partitioned datasets profile only the partition which matches the datetime or profile the latest one if not set. Only Bigquery supports this. |