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Posted to commits@doris.apache.org by GitBox <gi...@apache.org> on 2020/02/20 11:09:29 UTC
[GitHub] [incubator-doris] vagetablechicken edited a comment on issue #2780:
OlapTableSink::send is low efficient?
vagetablechicken edited a comment on issue #2780: OlapTableSink::send is low efficient?
URL: https://github.com/apache/incubator-doris/issues/2780#issuecomment-588156273
# OlapTableSink Multithreading Solution Design
## single-thread model (original model)
## multi-thread model
When we create an OlapTableSink, prepare N buffers and N send threads.
If a row needs to be added to NodeChannel(node_id=A, only consider node_id), the main thread copy it to buffer A%N.
We can limit the buffer size(use MemTracker), the mem_limit is configurable. If a buffer is full, we block adding rows to this buffer , until all rows in buffer have been consumed.
### Extra cost of multi-thread ver
thread: buffer_num
mem: buffer_num*(mem_limit+buffer_running_mem)
### single/multi version switch
The acceleration effect is evident for large data imports. But no need for every OlapTableSink.
So I design it:
We can select origin(single-thread) version or multi-thread version by set broker load property, and configure the buffer_num & mem_limit_per_buffer.
We add fields to TOlapTableSink, like
```
struct TOlapTableSink {
...
14: optional i64 load_channel_timeout_s // the timeout of load channels in second
15: optional i32 buffer_num
16: optional i64 mem_limit_per_buf
17: optional i64 size_limit_per_buf
}
```
`buffer_num > 0` means using "multi-thread & buffer" mode.
`buffer_num = 0` or not set means using "single-thread" mode(the origin mode).
(`buffer_num = 1` is hard to define. We should avoid setting buffer_num to 1.)
So we can use
```
LOAD LABEL ...
PROPERTIES
(
"buffer_num"="5",
"mem_limit_per_buf"="5368709120",
"size_limit_per_buf"="62914560"
);
```
# A Test Case
cluster: 5 be
{"ScannedRows":895737370,"TaskNumber":1,"FileNumber":300,"FileSize":60216822679} // 56G
## origin ver
| LoadStartTime | LoadFinishTime |
|----|----|
| 2020-02-19 20:44:00 | 2020-02-20 00:35:01 |
## multi-thread ver
buffer_num/mem_limit_per_buf/size_limit_per_buf = 5/1G/30M
| LoadStartTime | LoadFinishTime |
|----|----|
| 2020-02-18 17:57:38 | 2020-02-18 20:05:13 |
buffer_num/mem_limit_per_buf/size_limit_per_buf = 5/5G/30M
| LoadStartTime | LoadFinishTime |
|----|----|
| 2020-02-18 20:14:58 | 2020-02-18 22:19:54 |
buffer_num/mem_limit_per_buf/size_limit_per_buf = 5/5G/60M
| LoadStartTime | LoadFinishTime |
|----|----|
| 2020-02-18 22:28:08 | 2020-02-19 00:36:28 |
## Test Analysis
56G broker load, the origin ver will run for 4 hours, the multi-ver can halve the time.
But increasing mem_limit & size_limit doesn't do much good.(not bad, cause we can only use minimum mem, the more memory is waste. 😀 )
1. Because we use modular hashing(node_id%buffer_num), the buffer_num should <= be_num.
buffer_num=be_num is ideal.
1. In single-thread ver, we only have a thread to add_batch/wait_packet. In multi-thread ver, we have buffer_num thread to do them. But the add_batch/wait_packet in one thread are in sequence, can't save time in one thread. Thus, the `actual consume` time is the ideal of load run time. For example,
`mem_handle: 3506.55s, deep_copy: 22.1017s, spsc push block if full: 7.81192s, consume: 7298.54s, actual consume: 7285s.` means the ideal run time is 7285s, our configuration can make the process 7298s. It means little to further optimize.
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