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Update altinity-kb-aggressive_merges.md
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content/en/altinity-kb-setup-and-maintenance/altinity-kb-aggressive_merges.md

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@@ -24,7 +24,7 @@ Additionally, you can:
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- disable direct io for big merges (min_merge_bytes_to_use_direct_io) - direct io is often slower (it bypasses the page cache, and it is used there to prevent pushing out the often used data from the cache by the running merge).
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- on a replicated system with slow merges and a fast network you can use execute_merges_on_single_replica_time_threshold
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- analyze if the Vertical or Horizontal merge is better / faster for your case/schema. (Vertical first merges the columns from the table ORDER BY and then other columns one by another - that normally requires less ram, and keep fewer files opened, but requires more complex computations compared to horizontal when all columns are merged simultaneously).
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- if you have a lot of tables - you can give also give more resources to the scheduler (the component which assigns the merges, and do some housekeeping) - background_schedule_pool_size & background_common_pool_size
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- if you have a lot of tables - you can also give more resources to the scheduler (the component which assigns the merges, and do some housekeeping) - background_schedule_pool_size & background_common_pool_size
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- review the schema, especially codes/compression used (they allow to reduce the size, but often can impact the merge speed significantly).
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- try to form bigger parts when doing inserts (min_insert_block_size_bytes / min_insert_block_size_rows / max_insert_block_size)
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- check if wide (every column in a separate file) or compact (columns are mixed in one file) parts are used (system.parts). By default min_bytes_for_wide_part=10 mln rows (so if the part is bigger that that the wide format will be used, compact otherwise). Sometimes it can be beneficial to use a compact format even for bigger parts (a lot of relatively small columns) or oppositely - use a wide format even for small parts (few fat columns in the table).

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