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update doc format
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liunaijie committed Aug 6, 2024
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Expand Up @@ -60,7 +60,7 @@ supports query SQL and can achieve projection effect.
| table_list | Array | No | - | The list of tables to be read, you can use this configuration instead of `table_path` |
| where_condition | String | No | - | Common row filter conditions for all tables/queries, must start with `where`. for example `where id > 100` |
| split.size | Int | No | 8096 | How many rows in one split, captured tables are split into multiple splits when read of table. |
| split.hash-function | String | No | - | Which hash function use to split. <br/> Default is `MD5`, Oracle is `ORA_HASH`, PostgreSQL is `HASHTEXT`.<br/> If the default function is not work, you can use this parameter to customize the hash function. | |
| split.hash-function | String | No | - | Which hash function use to split. <br/> Default is `MD5`, Oracle is `ORA_HASH`, PostgreSQL is `HASHTEXT`.<br/> If the default function is not work, you can use this parameter to customize the hash function. | |
| split.even-distribution.factor.lower-bound | Double | No | 0.05 | Not recommended for use.<br/> The lower bound of the chunk key distribution factor. This factor is used to determine whether the table data is evenly distributed. If the distribution factor is calculated to be greater than or equal to this lower bound (i.e., (MAX(id) - MIN(id) + 1) / row count), the table chunks would be optimized for even distribution. Otherwise, if the distribution factor is less, the table will be considered as unevenly distributed and the sampling-based sharding strategy will be used if the estimated shard count exceeds the value specified by `sample-sharding.threshold`. The default value is 0.05. |
| split.even-distribution.factor.upper-bound | Double | No | 100 | Not recommended for use.<br/> The upper bound of the chunk key distribution factor. This factor is used to determine whether the table data is evenly distributed. If the distribution factor is calculated to be less than or equal to this upper bound (i.e., (MAX(id) - MIN(id) + 1) / row count), the table chunks would be optimized for even distribution. Otherwise, if the distribution factor is greater, the table will be considered as unevenly distributed and the sampling-based sharding strategy will be used if the estimated shard count exceeds the value specified by `sample-sharding.threshold`. The default value is 100.0. |
| split.sample-sharding.threshold | Int | No | 1000 | This configuration specifies the threshold of estimated shard count to trigger the sample sharding strategy. When the distribution factor is outside the bounds specified by `chunk-key.even-distribution.factor.upper-bound` and `chunk-key.even-distribution.factor.lower-bound`, and the estimated shard count (calculated as approximate row count / chunk size) exceeds this threshold, the sample sharding strategy will be used. This can help to handle large datasets more efficiently. The default value is 1000 shards. |
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