After the outer catch exception, faststring resize reserve build may throw a memory alloc failure exception from the Allocator.
Currently page body compress will catch memory alloc failure exception
Currently, there are some useless includes in the codebase. We can use a tool named include-what-you-use to optimize these includes. By using a strict include-what-you-use policy, we can get lots of benefits from it.
When the system MemAvailable is less than the warning water mark, or the memory used by the BE process exceeds the mem soft limit, run minor gc and try to release cache.
When the MemAvailable of the system is less than the low water mark, or the memory used by the BE process exceeds the mem limit, run fucc gc, try to release the cache, and start canceling from the query with the largest memory usage until the memory of mem_limit * 20% is released.
mem tracker can be logically divided into 4 layers: 1)process 2)type 3)query/load/compation task etc. 4)exec node etc.
type includes
enum Type {
GLOBAL = 0, // Life cycle is the same as the process, e.g. Cache and default Orphan
QUERY = 1, // Count the memory consumption of all Query tasks.
LOAD = 2, // Count the memory consumption of all Load tasks.
COMPACTION = 3, // Count the memory consumption of all Base and Cumulative tasks.
SCHEMA_CHANGE = 4, // Count the memory consumption of all SchemaChange tasks.
CLONE = 5, // Count the memory consumption of all EngineCloneTask. Note: Memory that does not contain make/release snapshots.
BATCHLOAD = 6, // Count the memory consumption of all EngineBatchLoadTask.
CONSISTENCY = 7 // Count the memory consumption of all EngineChecksumTask.
}
Object pointers are no longer saved between each layer, and the values of process and each type are periodically aggregated.
other fix:
In [fix](memtracker) Fix transmit_tracker null pointer because phamp is not thread safe #13528, I tried to separate the memory that was manually abandoned in the query from the orphan mem tracker. But in the actual test, the accuracy of this part of the memory cannot be guaranteed, so put it back to the orphan mem tracker again.
disable page cache by default
disable chunk allocator by default
not use chunk allocator for vectorized allocator by default
add a new config memory_linear_growth_threshold = 128Mb, not allocate memory by RoundUpToPowerOf2 if the allocated size is larger than this threshold. This config is added to MemPool, ChunkAllocator, PodArray, Arena.
Disable Chunk Allocator in Vectorized Allocator, this will reduce memory cache.
For high concurrent queries, using Chunk Allocator with vectorized Allocator can reduce the impact of gperftools tcmalloc central lock.
Jemalloc or google tcmalloc have core cache, Chunk Allocator may no longer be needed after replacing gperftools tcmalloc.
1. Fix LoadTask, ChunkAllocator, TabletMeta, Brpc, the accuracy of memory track.
2. Modified some MemTracker names, deleted some unnecessary trackers, and improved readability.
3. More powerful MemTracker debugging capabilities.
4. Avoid creating TabletColumn temporary objects and improve BE startup time by 8%.
5. Fix some other details.
1. fix track bthread
- Bthread, a high performance M:N thread library used by brpc. In Doris, a brpc server response runs on one bthread, possibly on multiple pthreads. Currently, MemTracker consumption relies on pthread local variables (TLS).
- This caused pthread TLS MemTracker confusion when switching pthread TLS MemTracker in brpc server response. So replacing pthread TLS with bthread TLS in the brpc server response saves the MemTracker.
Ref: 731730da85/docs/en/server.md (bthread-local)
2. fix track vectorized query
- Added track mmap. Currently, mmap allocates memory in many places of the vectorized execution engine.
- Refactored ThreadContext to avoid dependency conflicts and make it easier to debug.
- Fix some bugs.
In pr #8476, all memory usage of a process is recorded in the process mem tracker,
and all memory usage of a query is recorded in the query mem tracker,
and it is still necessary to manually call `transfer to` to track the cached memory size.
We hope to separate out more detailed memory usage based on Hook TCMalloc new/delete + TLS mem tracker.
In this pr, the more detailed mem tracker is switched to TLS, which automatically and accurately
counts more detailed memory usage than before.
Early Design Documentation: https://shimo.im/docs/DT6JXDRkdTvdyV3G
Implement a new way of memory statistics based on TCMalloc New/Delete Hook,
MemTracker and TLS, and it is expected that all memory new/delete/malloc/free
of the BE process can be counted.
Modify the implementation of MemTracker:
1. Simplify a lot of useless logic;
2. Added MemTrackerTaskPool, as the ancestor of all query and import trackers, This is used to track the local memory usage of all tasks executing;
3. Add cosume/release cache, trigger a cosume/release when the memory accumulation exceeds the parameter mem_tracker_consume_min_size_bytes;
4. Add a new memory leak detection mode (Experimental feature), throw an exception when the remaining statistical value is greater than the specified range when the MemTracker is destructed, and print the accurate statistical value in HTTP, the parameter memory_leak_detection
5. Added Virtual MemTracker, cosume/release will not sync to parent. It will be used when introducing TCMalloc Hook to record memory later, to record the specified memory independently;
6. Modify the GC logic, register the buffer cached in DiskIoMgr as a GC function, and add other GC functions later;
7. Change the global root node from Root MemTracker to Process MemTracker, and remove Process MemTracker in exec_env;
8. Modify the macro that detects whether the memory has reached the upper limit, modify the parameters and default behavior of creating MemTracker, modify the error message format in mem_limit_exceeded, extend and apply transfer_to, remove Metric in MemTracker, etc.;
Modify where MemTracker is used:
1. MemPool adds a constructor to create a temporary tracker to avoid a lot of redundant code;
2. Added trackers for global objects such as ChunkAllocator and StorageEngine;
3. Added more fine-grained trackers such as ExprContext;
4. RuntimeState removes FragmentMemTracker, that is, PlanFragmentExecutor mem_tracker, which was previously used for independent statistical scan process memory, and replaces it with _scanner_mem_tracker in OlapScanNode;
5. MemTracker is no longer recorded in ReservationTracker, and ReservationTracker will be removed later;
BitShufflePageDecoder reuses the memory for storing decoder results, allocate memory directly from the
`ChunkAllocator`, the performance is improved to a certain extent.
In the case of #6285, the total time consumption is reduced by 13.5%, and the time consumption ratio of `~Reader()`
has also been reduced from 17.65% to 1.53%, and the memory allocation is unified to `ChunkAllocator` for centralized
management , Which is conducive to subsequent memory optimization.
which can avoid the memory waste caused by `Mempool`, because the chunk can be free at any time, but the
performance is lower than the allocation from `Mempool`. The guess is that there is no `Mempool` after secondary
allocation of large chunks , Will directly apply for a large number of small chunks from `ChunkAllocator`, and it takes
longer to lock in `pop_free_chunk` and `push_free_chunk` (but this is not proven from the flame graphs of BE's cpu and
contention).
Sometimes we want to detect the hotspot of a cluster, for example, hot scanned tablet, hot wrote tablet,
but we have no insight about tablets in the cluster.
This patch introduce tablet level metrics to help to achieve this object, now support 4 metrics on tablets: `query_scan_bytes `, `query_scan_rows `, `flush_bytes `, `flush_count `.
However, one BE may holds hundreds of thousands of tablets, so I add a parameter for the metrics HTTP request,
and not return tablet level metrics by default.
Redesign metrics to 3 layers:
MetricRegistry - MetricEntity - Metrics
MetricRegistry : the register center
MetricEntity : the entity registered on MetricRegistry. Generally a MetricRegistry can be registered on several
MetricEntities, each of MetricEntity is an independent entity, such as server, disk_devices, data_directories, thrift
clients and servers, and so on.
Metric : metrics of an entity. Such as fragment_requests_total on server entity, disk_bytes_read on a disk_device entity,
thrift_opened_clients on a thrift_client entity.
MetricPrototype: the type of a metric. MetricPrototype is a global variable, can be shared by the same metrics across
different MetricEntities.
Add a JSON format for existing metrics like this.
```
{
"tags":
{
"metric":"thread_pool",
"name":"thrift-server-pool",
"type":"active_thread_num"
},
"unit":"number",
"value":3
}
```
I add a new JsonMetricVisitor to handle the transformation.
It's not to modify existing PrometheusMetricVisitor and SimpleCoreMetricVisitor.
Also I add
1. A unit item to indicate the metric better
2. Cloning tablet statistics divided by database.
3. Use white space to replace newline in audit.log
I add ChunkAllocator in this CL to put unused memory chunk to a chunk
pool other than return it to system allocator. Now we only change
MemPool's chunk allocation and free to this.
And two configuration are introduduced too. 'chunk_reserved_bytes_limit'
is the limit of how many bytes this chunk pool can reserve in total and
its default value is 2147483648(2GB). 'use_mmap_allocate_chunk': if
chunk is allocated via mmap and default value is false.
And in my test case with default configuration a simple like
"select * from table limit 10", this can improve throughput from 280 QPS
to to 650 QPS. And when I config 'chunk_reserved_bytes_limit' to 0,
which means this is disabled, the throughput is the same with origin's.
