Manually track query/load/compaction/etc. memory in Allocator instead of mem hook.
Can still use Mem Hook when cannot manually track memory code segments and find memory locations during debugging.
This will cause memory tracking loss for Query, loss less than 10% compared to the past, but this is expected to be more controllable.
Similarly, Mem Hook will no longer track unowned memory to the orphan mem tracker by default, so the total memory of all MemTrackers will be less than before.
Not need to get memory size from jemalloc in Mem Hook each memory alloc and free, which would lose performance in the past.
Not require caching bthread local in pthread local for memory hook, in the past this has caused core dumps inside bthread, seems to be a bug in bthread.
ThreadContext life cycle to manual control
In the past, ThreadContext was automatically created when it was used for the first time (this was usually in the Jemalloc Hook when the first malloc memory), and was automatically destroyed when the thread exited.
Now instead of manually controlling the create and destroy of ThreadContext, it is mainly created manually when the task thread start and destroyed before the task thread end.
Run 43 clickbench query tests.
Use MemHook in the past:
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.
# Proposed changes
This PR fixed lots of issues when building from source on macOS with Apple M1 chip.
## ATTENTION
The job for supporting macOS with Apple M1 chip is too big and there are lots of unresolved issues during runtime:
1. Some errors with memory tracker occur when BE (RELEASE) starts.
2. Some UT cases fail.
...
Temporarily, the following changes are made on macOS to start BE successfully.
1. Disable memory tracker.
2. Use tcmalloc instead of jemalloc.
This PR kicks off the job. Guys who are interested in this job can continue to fix these runtime issues.
## Use case
```shell
./build.sh -j 8 --be --clean
cd output/be/bin
ulimit -n 60000
./start_be.sh --daemon
```
## Something else
It takes around _**10+**_ minutes to build BE (with prebuilt third-parties) on macOS with M1 chip. We will improve the development experience on macOS greatly when we finish the adaptation job.
1. replace all boost::shared_ptr to std::shared_ptr
2. replace all boost::scopted_ptr to std::unique_ptr
3. replace all boost::scoped_array to std::unique<T[]>
4. replace all boost:thread to std::thread
At present, the application of vlog in the code is quite confusing.
It is inherited from impala VLOG_XX format, and there is also VLOG(number) format.
VLOG(number) format does not have a unified specification, so this pr standardizes the use of VLOG
ThreadSanitizer, aka TSAN, is a useful tool to detect multi-thread
problems, such as data race, mutex problems, etc.
We should detect TSAN problems for Doris BE, both unit tests and
server should pass through TSAN mode, to make Doris more robustness.
This is the very beginning patch to fix TSAN problems, and some
difficult problems are suppressed in file 'tsan_suppressions', you
can suppress these problems by setting:
export TSAN_OPTIONS="suppressions=tsan_suppressions"
before running:
`BUILD_TYPE=tsan ./run-be-ut.sh --run`
This CL mainly includes:
- add some methods to get thread's stats from Linux's system file in
env.
- support get thread's stats by http method.
- register page handle in BE to show thread's stats to help developer
position some thread relate problem.
Thread pool design point:
All tasks submitted directly to the thread pool enter a FIFO queue and are
dispatched to a worker thread when one becomes free. Tasks may also be
submitted via ThreadPoolTokens. The token wait() and shutdown() functions
can then be used to block on logical groups of tasks.
A token operates in one of two ExecutionModes, determined at token
construction time:
1. SERIAL: submitted tasks are run one at a time.
2. CONCURRENT: submitted tasks may be run in parallel.
This isn't unlike submitted without a token, but the logical grouping that tokens
impart can be useful when a pool is shared by many contexts (e.g. to
safely shut down one context, to derive context-specific metrics, etc.).
Tasks submitted without a token or via ExecutionMode::CONCURRENT tokens are
processed in FIFO order. On the other hand, ExecutionMode::SERIAL tokens are
processed in a round-robin fashion, one task at a time. This prevents them
from starving one another. However, tokenless (and CONCURRENT token-based)
tasks can starve SERIAL token-based tasks.
Thread design point:
1. It is a thin wrapper around pthread that can register itself with the singleton ThreadMgr
(a private class implemented in thread.cpp entirely, which tracks all live threads so
that they may be monitored via the debug webpages). This class has a limited subset of
boost::thread's API. Construction is almost the same, but clients must supply a
category and a name for each thread so that they can be identified in the debug web
UI. Otherwise, join() is the only supported method from boost::thread.
2. Each Thread object knows its operating system thread ID (TID), which can be used to
attach debuggers to specific threads, to retrieve resource-usage statistics from the
operating system, and to assign threads to resource control groups.
3. Threads are shared objects, but in a degenerate way. They may only have
up to two referents: the caller that created the thread (parent), and
the thread itself (child). Moreover, the only two methods to mutate state
(join() and the destructor) are constrained: the child may not join() on
itself, and the destructor is only run when there's one referent left.
These constraints allow us to access thread internals without any locks.
