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.
Refactor TaggableLogger
Refactor status handling in agent task:
Unify log format in TaskWorkerPool
Pass Status to the top caller, and replace some OLAPInternalError with more detailed error message Status
Premature return with the opposite condition to reduce indention
1. solved the previous delayed unit test file size is too large (1.7G+) and the unit test link time is too long problem problems
2. Unify all unit tests into one file to significantly reduce unit test execution time to less than 3 mins
3. temporarily disable stream_load_test.cpp, metrics_action_test.cpp, load_channel_mgr_test.cpp because it will re-implement part of the code and affect other tests
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
For PR #5792. This patch add a new param `cache type` to distinguish sql cache and partition cache.
When update sql cache, we make assure one sql key only has one version cache.
There are some long loops and sleeps in unit tests, it will cost a
very long time to run all unit tests, especially run in TSAN mode.
This patch speed up unit tests by shortening long loops and sleeps,
on my environment all unit tests finished in 1 minite. It's useful
to do basic functional unit tests.
You can switch to run in this mode by adding a new environment variable
'DORIS_ALLOW_SLOW_TESTS'. For example, you can set:
export DORIS_ALLOW_SLOW_TESTS=1
and also you can disable it by setting:
export DORIS_ALLOW_SLOW_TESTS=0
When partition cache is not cached continuely, range query may fail.
For example, partition key 20201011 and 20201013 is cached,
but rang query is between 20201011 and 20201013, the query will not hit the cache.
issue:#5059
* When the different partition of the table is updated frequently, the partition key list of the cache is discontinuous,
and the partition key in the request cannot hit the key list in the cache, resulting in the access overrun，the BE will crash.
* Add some unit test case，add test cases that fail to hit the boundary value of cache
1. Find the cache node by SQL Key, then find the corresponding partition data by Partition Key, and then decide whether to hit Cache by LastVersion and LastVersionTime
2. Refers to the classic cache algorithm LRU, which is the least recently used algorithm, using a three-layer data structure to achieve
3. The Cache elimination algorithm is implemented by ensuring the range of the partition as much as possible, to avoid the situation of partition discontinuity, which will reduce the hit rate of the Cache partition,
4. Use the two thresholds of maximum memory and elastic memory to control to avoid frequent elimination of data
