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[SIGMOD '24] CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated Infrastructure

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[SIGMOD'24] CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated Infrastructure

Paper

CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated Infrastructure

Qiaolin Yu, Chang Guo, Jay Zhuang, Viraj Thakkar, Jianguo Wang, Zhichao Cao.

ACM Conference on Management of Data (SIGMOD 2024), Research Track Full Paper.

Dependencies

Baselines

  • Notice that multiple CSAs should bind with one Control Plane.
  • Please install the required dependencies before trying to compile.
  • Note that currently we only support cmake. Do not use the makefile directly.

Rocks-Local

Search the repository for this code and delete it.

tmp_options.compaction_service = std::make_shared<MyTestCompactionService>(
      dbname, compaction_options, compaction_stats, remote_listeners,
      remote_table_properties_collector_factories);

CaaS-LSM

  • Config the address of Control Plane, CSA, and HDFS server in include/rocksdb/options.h
  • Build and compile
  • Run Control Plane and CSA
git clone [email protected]:asu-idi/CaaS-LSM.git
cd CaaS-LSM
mkdir build
cd build
cmake ..
make -j100
./procp_server #run Control Plane server
./csa_server #run CSA server

Disaggre-RocksDB

  • Config the address of CSA, and HDFS server in include/rocksdb/options.h
  • Build and compile
  • Run CSA
git clone [email protected]:asu-idi/CaaS-LSM.git
cd CaaS-LSM
git checkout disaggre-rocksdb
mkdir build
cd build
cmake ..
make -j100
./csa_server # The name is the same, but the function of CSA is different with that of CaaS-LSM

Terark-Local

Terark-Native

  • checkout branch to terark-native
sudo apt-get install libaio-dev
  • Before building, open WITH_TOOLS and WITH_TERARK_ZIP, it's neccessary for remote compaction mode.
./build.sh
  • Use remote_compaction_worker_101

Terark-CaaS

  • Copy the code in db/compaction/remote_compaction of CaaS-LSM, including procp_server.cc, csa_server.cc, utils.h, compaction_service.proto
  • Change CompactionArgs to string, since TerarkDB uses encoded string in network transmit.
  • Use the same way in CaaS-LSM to start.

To evaluate the baselines

Run db_bench

./db_bench --benchmarks="fillrandom" --num=4000000 --statistics --threads=16 --max_background_compactions=8 --db=/xxx/xxx  --statistics

OPS comparison

ops

P99 latency comparison

p99

Conclusion

The OPS of CaaS-LSM surpassed Disaggre-RocksDB by up to 61%, and TerarkDB-CaaS surpassed native TerarkDB up to 42%.

Test CaaS-LSM in distributed applications

Test Nebula

Test Kvrocks

  • Clone Kvrocks at https://github.com/apache/incubator-kvrocks

  • Before build:

    • modify this part in "cmake/rocksdb.cmake" to switch the branch of the default RocksDB to this repository
    FetchContent_DeclareGitHubWithMirror(rocksdb
       facebook/rocksdb v7.8.3
       MD5=f0cbf71b1f44ce8f50407415d38b9d44
     )
    
  • Build: ./x.py build

  • Single mode:

    • build/kvrocks -c kvrocks.conf
  • Cluster mode:

    • Based on kvrocks controller https://github.com/KvrocksLabs/kvrocks_controller.git with commit df83752849ef41ce91037ca5c9cc6c670a480d56
    • Dependencies: etcd https://etcd.io/docs/v3.5/install/
    • Build kvrocks controller: make
    • Start controller server: ./_build/kvrocks-controller-server -c ./config/config.yaml
    • A fast way to build cluster: python scripts/e2e_test.py
    • Check cluster status: ./_build/kvrocks-controller-cli -c ./config/kc_cli_config.yaml
    • modify kvrocks.conf: port(e.g., 30001-30006), cluster-enabled(yes), dir /tmp/kvrocks(/tmp/kvrocks1-6)

Evaluation Results

OPS of Nebula

nebula_sche_ops

Latency of Nebula

nebula_sche_latency

Conclusion

Nebula-Random-Sche has a total OPS of 5,669 and an average latency of 526 ms, which are about 86% lower and 6$X$ higher than Nebula-CaaS-LSM respectively.

OPS of Kvrocks

kvrocks_ops_new_2

Latency of Kvrocks

kvrocks_latency_new_2

Conclusion

With better scheduling of compaction jobs in Kvrocks-CaaS, the overall OPS is about 20% better than that of Kvrocks-Local, and the average latency improves by 30%. In the cross-datacenter scenario, according to the log file, Kvrocks-Local experiences compaction jobs piled and a severe write slowdown after intensive compaction starts. In contrast, Kvrocks-CaaS runs smoothly and improves the overall OPS by 28% and P99 latency by 65%.

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[SIGMOD '24] CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated Infrastructure

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GPL-2.0 and 2 other licenses found

Licenses found

GPL-2.0
COPYING
Apache-2.0
LICENSE.Apache
Unknown
LICENSE.leveldb

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