Validity Tracking Based Log Management for In-Memory Databases

Abstract

With in-memory databases (IMDBs), where all data sets reside in main memory for fast processing speed, logging and checkpointing are essential for achieving persistence in data. Logging of IMDBs has evolved to reduce run-time overhead to suit the systems, but this causes an increase in recovery time. Checkpointing technique compensates for these problems with logging, but existing schemes often incur high costs due to reduced system throughput, increased latency, and increased memory usage. In this paper, we propose a checkpointing scheme using validity tracking-based compaction (VTC), the technique that tracks the validity of logs in a file and removes unnecessary logs. The proposed scheme shows extremely low memory usage compared to existing checkpointing schemes, which use consistent snapshots. Our experiments demonstrate that checkpoints using consistent snapshot increase memory footprint by up to two times in update-intensive workloads. In contrast, our proposed VTC only requires 2% additional memory for checkpointing. That means the system can use most of its memory to store data and process transactions.