hbaseconasia2019 Test-suite for Automating Data-consistency checks on HBase
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The document discusses a test-suite developed by Flipkart for automating data-consistency checks on their HBase cluster, essential for supporting their large e-commerce operations. It highlights the need for data-correctness guarantees and details various approaches to testing, including algorithm and code testing as well as testing on a running cluster. The suite aims to facilitate faster upgrade cycles and addresses potential failure scenarios and issues uncovered during testing.
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hbaseconasia2019 HBase Bucket Cache on Persistent Memory
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hbaseconasia2019 BDS: A data synchronization platform for HBase
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国外留学无法毕业的留学生（即没有获得毕业证书和学位证书的情况下）想要在中国进行学历认证，通常不能通过正常的学历认证流程进行认证，因为正常的学历认证需要提供有效的毕业证书和学位证书，以及其他相关的学业文件。
在这种情况下，留学生可以选择通过留学服务中心的留信认证来尝试认证他们的学习经历。具体来说，留信认证是针对没有获得正规学位或毕业证书的学生，通过提供学习经历、课程成绩等材料，进行学业经历的认证。
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hbaseconasia2019 Test-suite for Automating Data-consistency checks on HBase
- 1. Test-suite for Automating Data-consistency checks on HBase Pradeep S, Mallikarjun V Flipkart
- 2. • India’s largest online retailer: • 10M page visits a day • 2M shipments a day • 30M products across more than 70 categories • Big Billion Days ($300M sales, top ranked app on Google Play Store) About Flipkart
- 3. Agenda ● Yak: HBase Cluster @ Flipkart ○ Need for scalable, multi-tenant, strongly consistent data stores ● Yak: Need for Data-correctness Guarantees ● Why Data-consistency Test-suite? ● How we did the Test-suite?
- 4. Yak: HBase Cluster @ Flipkart ● HBase for OLTP Key-Value store ● Bring-Your-Own-Box multi-tenancy on HBase ● RSGroup based isolation on HBase 1.2.4 & 2.1.3 ● WAL based Change-Data-Capture into Kafka ● Stores critical data-sets in e-commerce like: Orders, Payments
- 5. Yak: Data-correctness Guarantees Required ● Read-Your-Own-Write consistency at single row level ● ‘Atleast-once’ guarantee in the change-data-capture ● Ordering guarantee in the change-data-capture ● Predictable recovery times, no data-loss upon failures ● Data-reliability for HBase admin operations
- 6. Why Data-consistency Test-suite? ● To enable faster upgrade cycles ● Releases dont degrading on the data-guarantees ● To assist in reproducing edge-cases scenarios ● To accommodate additional failure scenarios
- 7. Different Approaches for the Test-suite ● Algorithm testing: TLA+, etc. ● Code testing: Test suite of HBase, Hadoop, Zookeeper ● Testing on running cluster: Jepsen, ChaosMonkey & ITBLL of HBase, etc.
- 8. Different Approaches for the Test-suite ● Algorithm testing: TLA+, etc. - Implementation, Deployment NOT tested ● Code testing: Test suite of HBase - Deployment, Integration NOT tested ● Testing on running cluster: Jepsen, ChaosMonkey & ITBLL of HBase, etc. Reason: Integrated test with { Algorithm + Code + Deployment }
- 9. Test-Suite ● Jepsen, ChaosMonkey based ● Test workload on HBase ● Simulated Interrupts: ○ Infrastructure failures ○ HBase component failures ○ Admin operations ● Test Report
- 10. Test-Suite - Test Workload ● Writes using CheckAndPut ● Observation points: ○ HBase Get ○ Kafka consumer from CDC
- 11. Test-Suite - Test Workload Generate Row Key1 CheckPut col:v = 1 Save Locally Get CheckPut col:v = 2 Save Locally Get CheckPut col:v = 3 Save Locally Get …... Thread-1 rowkey = “key1” col:v = 1 rowkey = “key1” col:v = 2 rowkey = “key1” col:v = 3 ….
- 12. Test-Suite - Test Workload Generate Row-Key1 CheckPut col:v = 1 Save Locally Get CheckPut col:v = 2 Save Locally Get CheckPut col:v = 3 Save Locally Get …... Thread-1 Generate Row-Key2 CheckPut col:v = 1 Save Locally Get CheckPut col:v = 2 Save Locally Get CheckPut col:v = 3 Save Locally Get …... Thread-2 Generate Row-Key3 CheckPut col:v = 1 Save Locally Get CheckPut col:v = 2 Save Locally Get CheckPut col:v = 3 Save Locally Get …... Thread-3 N Threads… on M Machines
- 13. Test-Suite - Assertions Generate Row-Key1 CheckPut col:v = 1 Save Locally Get CheckPut col:v = 2 Save Locally Get CheckPut col:v = 3 Save Locally Get …... Thread-1 ● Locally saved-state is compared against Get call result for no data-loss For Key1 after every CheckAndPut: Assert ( ThreadLocal<Version> == Version from HBase )
- 14. Test-Suite - Assertions Generate Row-Key1 CheckPut col:v = 1 Save Locally Get CheckPut col:v = 2 Save Locally Get CheckPut col:v = 3 Save Locally Get …... Thread-1 ● Kafka listener reads the events of the key: For a key1 having writes as: 1,2,3,4 1,2,2,2,3,4 1,2,3,2,3,4 1,2,4,2,3,4 1,2,4 For the key1: Assert ( read event version <= latest seen version +1 )
- 15. Test-Suite - Assertions Generate Row-Key1 CheckPut col:v = 1 Save Locally Get CheckPut col:v = 2 Save Locally Get CheckPut col:v = 3 Save Locally Get …... Thread-1 ● HBase regions of a table are within the RSGroup nodes ● HDFS data-blocks stored within the RSGroup nodes Assert (Region Assignment within RSGroup Nodes) Assert (HDFS blocks within RSGroup Nodes)
- 16. Test-Suite - Assertions Generate Row-Key1 CheckPut col:v = 1 Save Locally Get CheckPut col:v = 2 Save Locally Get CheckPut col:v = 3 Save Locally Get …... Thread-1 ● Locally saved-state is compared against Get call result for no data-loss ● Kafka listener reads the events of the key: ○ To assert no data-loss as the versions are incremental ○ To assert no-ordering loss ● RSGroup isolation checks: WAL & HDFS data-blocks & Region Assignment
- 17. Interruptions ● Simulate issue & heal ● Types of Interruptions: ○ Infrastructure failures ○ HBase component failures ○ HBase admin operations
- 18. Interruptions - Infrastructure Failures ● Network failures: ○ Network partition/failure: within zookeeper, region-servers, namenode etc. ○ Packet loss: within zookeeper, master, region-servers, namenode etc. ○ Tools: iptables, tc, comcast ● Other failure modes - to be added: ○ Clock skew ○ Packet delays ○ Disk read-only etc
- 19. Interruptions - Component Failures ● Kill hbase components: ○ region-server, master-node, zookeeper ● Kill hadoop components: ○ data-node, journal-node, name-node ● Node crash: ○ region-server-node, master-node, name-node, zookeeper, journal-node
- 20. Interruptions - HBase Admin Operations ● Split/merge region ● Assign/move region ● Restart: region-server, data-node ● Stop: region-server, data-node, etc. ● Kafka properties reload for CDC
- 21. Issues Uncovered & Fixed ● Assign an already assigned region causing data-loss - Fixed in 2.x ● Ordering loss in tail process from WAL file upon a region failover - Fixed in 2.x ● WAL not-isolated across region-server group - HBASE-21641
- 22. ● Migration to HBase ChaosMonkey for Interruptions ● Opensource the test-suite ● WAL push to Kafka - https://github.com/flipkart-incubator/hbase-sep Further Plans
- 23. Thanks！
- 24. Appendix
- 25. ● Tests are not deterministic. Needs 100s of iterations. ● Doesn’t catch all the bugs. But catches the practical issues for the specific use-case. Limitations
- 26. Test-Suite - Sample Report