Hi all,
Ignite, when persistence mode is enabled, stores data and indexes on disk. To minimize the latency of disks, several tuning options can be applied. Setting the page size of a memory region to match the page size of the underlying storage, using a separate disk for the WAL, and using production-level SSDs are just a few of them [ https://apacheignite.readme.io/docs/durable-memory-tuning#section-native-persistence-related-tuning ]. A persistent memory store with low latency and high capacity offers a viable alternative to disks. In light of this, we are proposing to make use of our Low Level Persistent Library (LLPL), https://github.com/pmem/pcj/tree/master/LLPL, to offer a persistent memory storage for Ignite. At this point, we envision two distinct implementation options: 1. Data and indexes will continue to be stored in the off-heap memory but the disk will be replaced by a persistent memory. Since persistence memory in this option is not a file system, the logic currently offered by WAL file and the partition files would have to be implemented from scratch. 2. In this option, we eliminate the current check-point process and the WAL file. We will use a memory region defined by LLPL to store data and indexes. There will be no off-heap memory. DRAM will be exclusively used to store hot cache entries just like the on-heap cache is in the current implementation. In both cases, there are more details and subtleties that have to handled - e.g. the atomic and transactional guarantees offered. More clarifications will be given as we go along. And, feel free to provide your thoughts. Thanks, Mulugeta
