Overview
This article discusses the process of migrating data from HBase to TiDB at Pinterest with zero downtime. It outlines the challenges faced, strategies employed, and the outcomes achieved during this significant transition.
What You'll Learn
1
How to implement a double write strategy for database migration
2
Why reconciliation jobs are critical for maintaining data consistency during migration
3
When to use TiDB for high-volume data applications
Prerequisites & Requirements
- Understanding of database migration concepts and strategies
- Familiarity with TiDB and HBase(optional)
- Experience with data consistency and reconciliation processes(optional)
Key Questions Answered
What strategies were employed for data migration from HBase to TiDB?
The article outlines several strategies for data migration, including double writes, snapshot dumps, and change data capture (CDC) with Kafka. Each approach has its own trade-offs, with double writes being the simplest but slower, while CDC offers more complexity but better performance for large datasets.
How was data consistency verified during the migration?
Data consistency was verified by comparing the data in HBase and TiDB after migration, achieving a consistency rate of 99.999%. This was done through reconciliation jobs that checked for mismatches and ensured that any discrepancies were resolved by treating HBase as the source of truth.
What were the performance improvements after migrating to TiDB?
Post-migration, Pinterest experienced a 3x-5x reduction in p99 latency for reads, decreasing from 500 ms to 60 ms. This significant improvement highlights the efficiency of TiDB in handling high-volume read and write operations.
What challenges were faced during the TiDB deployment?
Challenges included managing the deployment without TiUP, leading to a steep learning curve in safe cluster management. Additionally, issues with data ingestion and the need for custom solutions to handle large datasets were encountered, requiring collaboration with the Pingcap team.
Key Statistics & Figures
Read p99 latency
500 ms to 60 ms
This improvement was observed after migrating from HBase to TiDB, showcasing the performance benefits of the new database system.
Data consistency rate
99.999%
Achieved through reconciliation processes during the migration from HBase to TiDB.
Data size migrated
4 TB
This was the size of the table being migrated, serving 14k read QPS and 400 write QPS.
Technologies & Tools
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Database
Hbase
Used as the original data storage system before migration.
Database
Tidb
Adopted as the new storage backend for Unified Storage Service.
Streaming
Kafka
Utilized for change data capture (CDC) during the migration process.
Data Processing
Mapreduce
Employed for processing and analyzing data during the migration.
Key Actionable Insights
1Implement a double write strategy to ensure data is written to both HBase and TiDB during migration.This approach allows for real-time data availability in TiDB while maintaining the existing HBase infrastructure, minimizing downtime and ensuring a smoother transition.
2Regularly run reconciliation jobs to maintain data consistency between HBase and TiDB.These jobs help identify and resolve discrepancies, ensuring that the migrated data remains accurate and reliable, which is crucial for operational integrity.
3Utilize snapshotting techniques to capture data states before migration.Taking snapshots allows for a reliable backup of the original data, facilitating easier recovery and validation during the migration process.
Common Pitfalls
1
Failing to properly manage double writes can lead to data inconsistencies.
If writes to one database succeed while failing in another, it can create discrepancies. Implementing robust reconciliation processes is essential to mitigate this risk.
2
Neglecting to monitor the performance impact of data ingestion on online traffic.
Data ingestion can consume significant resources, potentially affecting the performance of other services. It's crucial to plan and allocate resources accordingly to avoid service degradation.
Related Concepts
Database Migration Strategies
Data Consistency And Reconciliation
Change Data Capture (cdc)
Performance Optimization In Databases