Buffers the data to write in RAM, periodically flushing it to another table. During the read operation, data is read from the buffer and the other table simultaneously.
Also, if at least one `flush*` condition is met, a flush is initiated in the background. This differs from `max*` since `flush*` allows you to configure background flushes separately to avoid adding latency for `INSERT` queries into Buffer tables.
During the write operation, data is inserted into one or more random buffers (configured with `num_layers`). Or, if the data part to insert is large enough (greater than `max_rows` or `max_bytes`), it is written directly to the destination table, omitting the buffer.
The conditions for flushing the data are calculated separately for each of the `num_layers` buffers. For example, if `num_layers = 16` and `max_bytes = 100000000`, the maximum RAM consumption is 1.6 GB.
Creating a `merge.hits_buffer` table with the same structure as `merge.hits` and using the Buffer engine. When writing to this table, data is buffered in RAM and later written to the ‘merge.hits’ table. A single buffer is created and the data is flushed if either:
- 100 seconds have passed since the last flush (`max_time`) or
- 1 million rows have been written (`max_rows`) or
- 100 MB of data have been written (`max_bytes`) or
- 10 seconds have passed (`min_time`) and 10,000 rows (`min_rows`) and 10 MB (`min_bytes`) of data have been written
For example, if just one row has been written, after 100 seconds, it will be flushed, no matter what. But if many rows have been written, the data will be flushed sooner.
You can set empty strings in single quotation marks for the database and table name. This indicates the absence of a destination table. In this case, when the data flush conditions are reached, the buffer is simply cleared. This may be useful for keeping a window of data in memory.
Note that the Buffer table does not support an index. In other words, data in the buffer is fully scanned, which might be slow for large buffers. (For data in a subordinate table, the index that it supports will be used.)
If the set of columns in the Buffer table does not match the set of columns in a subordinate table, a subset of columns that exist in both tables is inserted.
If the types do not match for one of the columns in the Buffer table and a subordinate table, an error message is entered in the server log, and the buffer is cleared.
Running ALTER on the Buffer table in releases made before 26 Oct 2021 will cause a `Block structure mismatch` error (see [#15117](https://github.com/ClickHouse/ClickHouse/issues/15117) and [#30565](https://github.com/ClickHouse/ClickHouse/pull/30565)), so deleting the Buffer table and then recreating is the only option. Check that this error is fixed in your release before trying to run ALTER on the Buffer table.
`FINAL` and `SAMPLE` do not work correctly for Buffer tables. These conditions are passed to the destination table but are not used for processing data in the buffer. If these features are required, we recommend only using the Buffer table for writing while reading from the destination table.
When adding data to a Buffer table, one of the buffers is locked. This causes delays if a read operation is simultaneously being performed from the table.
Data that is inserted into a Buffer table may end up in the subordinate table in a different order and in different blocks. Because of this, a Buffer table is difficult to use for writing to a CollapsingMergeTree correctly. To avoid problems, you can set `num_layers` to 1.
If the destination table is replicated, some expected characteristics of replicated tables are lost when writing to a Buffer table. The random changes to the order of rows and sizes of data parts cause data deduplication to quit working, which means it is not possible to have a reliable ‘exactly once’ write to replicated tables.
A Buffer table is used when too many INSERTs are received from a large number of servers over a unit of time, and data can’t be buffered before insertion, which means the INSERTs can’t run fast enough.
Note that it does not make sense to insert data one row at a time, even for Buffer tables. This will only produce a speed of a few thousand rows per second while inserting larger blocks of data can produce over a million rows per second.