5fc57eec2b
Summary: **Context:** Current `NonBatchedOpsStressTest` does not allow multi-thread read (i.e, Get, Iterator) and write (i.e, Put, Merge) or delete to the same key. Every read or write/delete operation will acquire lock (`GetLocksForKeyRange`) on the target key to gain exclusive access to it. This does not align with RocksDB's nature of allowing multi-thread read and write/delete to the same key, that is concurrent threads can issue read/write/delete to RocksDB without external locking. Therefore this is a gap in our testing coverage. To close the gap, biggest challenge remains in verifying db value against expected state in presence of parallel read and write/delete. The challenge is due to read/write/delete to the db and read/write to expected state is not within one atomic operation. Therefore we may not know the exact expected state of a certain db read, as by the time we read the expected state for that db read, another write to expected state for another db write to the same key might have changed the expected state. **Summary:** Credited to ajkr's idea, we now solve this challenge by breaking the 32-bits expected value of a key into different parts that can be read and write to in parallel. Basically we divide the 32-bits expected value into `value_base` (corresponding to the previous whole 32 bits but now with some shrinking in the value base range we allow), `pending_write` (i.e, whether there is an ongoing concurrent write), `del_counter` (i.e, number of times a value has been deleted, analogous to value_base for write), `pending_delete` (similar to pending_write) and `deleted` (i.e whether a key is deleted). Also, we need to use incremental `value_base` instead of random value base as before because we want to control the range of value base a correct db read result can possibly be in presence of parallel read and write. In that way, we can verify the correctness of the read against expected state more easily. This is at the cost of reducing the randomness of the value generated in NonBatchedOpsStressTest we are willing to accept. (For detailed algorithm of how to use these parts to infer expected state of a key, see the PR) Misc: hide value_base detail from callers of ExpectedState by abstracting related logics into ExpectedValue class Pull Request resolved: https://github.com/facebook/rocksdb/pull/11058 Test Plan: - Manual test of small number of keys (i.e, high chances of parallel read and write/delete to same key) with equally distributed read/write/deleted for 30 min ``` python3 tools/db_crashtest.py --simple {blackbox|whitebox} --sync_fault_injection=1 --skip_verifydb=0 --continuous_verification_interval=1000 --clear_column_family_one_in=0 --max_key=10 --column_families=1 --threads=32 --readpercent=25 --writepercent=25 --nooverwritepercent=0 --iterpercent=25 --verify_iterator_with_expected_state_one_in=1 --num_iterations=5 --delpercent=15 --delrangepercent=10 --range_deletion_width=5 --use_merge={0|1} --use_put_entity_one_in=0 --use_txn=0 --verify_before_write=0 --user_timestamp_size=0 --compact_files_one_in=1000 --compact_range_one_in=1000 --flush_one_in=1000 --get_property_one_in=1000 --ingest_external_file_one_in=100 --backup_one_in=100 --checkpoint_one_in=100 --approximate_size_one_in=0 --acquire_snapshot_one_in=100 --use_multiget=0 --prefixpercent=0 --get_live_files_one_in=1000 --manual_wal_flush_one_in=1000 --pause_background_one_in=1000 --target_file_size_base=524288 --write_buffer_size=524288 --verify_checksum_one_in=1000 --verify_db_one_in=1000 ``` - Rehearsal stress test for normal parameter and aggressive parameter to see if such change can find what existing stress test can find (i.e, no regression in testing capability) - [Ongoing]Try to find new bugs with this change that are not found by current NonBatchedOpsStressTest with no parallel read and write/delete to same key Reviewed By: ajkr Differential Revision: D42257258 Pulled By: hx235 fbshipit-source-id: e6fdc18f1fad3753e5ac91731483a644d9b5b6eb |
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RocksDB: A Persistent Key-Value Store for Flash and RAM Storage
RocksDB is developed and maintained by Facebook Database Engineering Team. It is built on earlier work on LevelDB by Sanjay Ghemawat (sanjay@google.com) and Jeff Dean (jeff@google.com)
This code is a library that forms the core building block for a fast key-value server, especially suited for storing data on flash drives. It has a Log-Structured-Merge-Database (LSM) design with flexible tradeoffs between Write-Amplification-Factor (WAF), Read-Amplification-Factor (RAF) and Space-Amplification-Factor (SAF). It has multi-threaded compactions, making it especially suitable for storing multiple terabytes of data in a single database.
Start with example usage here: https://github.com/facebook/rocksdb/tree/main/examples
See the github wiki for more explanation.
The public interface is in include/
. Callers should not include or
rely on the details of any other header files in this package. Those
internal APIs may be changed without warning.
Questions and discussions are welcome on the RocksDB Developers Public Facebook group and email list on Google Groups.
License
RocksDB is dual-licensed under both the GPLv2 (found in the COPYING file in the root directory) and Apache 2.0 License (found in the LICENSE.Apache file in the root directory). You may select, at your option, one of the above-listed licenses.