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Let's describe the B+ Tree in more detail to understand the need for invoke operation.
The keys of the tree (hashes) are stored on the B+ Tree pages (index pages), the cache key-value itself is stored on data pages. Each item on the index page includes a link to the data page item. In general, a B+ Tree supports find, put and remove operations. For put andremove, you must first find the point of insertion/update/removal. So, cache entry update without invoke operation can look like this:
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- Add support for MVCC (TRANSACTIONAL_SNAPSHOT) cache mode.
Risks and Assumptions
- In-memory eviction policy can be configured in such a way that will lead to OOM when using batch writing to data pages, so in some degenerate cases the batch writing must be disabled.
- For BPlusTree batch operations, ordered keys are required, moreover, an attempt to simultaneously lock the same keys in a different order lead to a deadlock, so batch insertion into the page memory must be performed on an unlocked entries. Alternatively, keys passed in batches from different components (preloader, datastreamer, putAll) should be locked in the same order.
- Heap usage/GC pressure.
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Jira |
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server | ASF JIRA |
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columns | key,summary,type,updated,assignee,reporter,priority,status,resolution |
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maximumIssues | 20 |
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jqlQuery | project = Ignite AND labels IN (iep-32) order by key |
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serverId | 5aa69414-a9e9-3523-82ec-879b028fb15b |
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The improvement in rebalancing time when using batch insertion is mostly noticeable when writing small objects and decreases with increasing object size.the improvement in total rebalancing time is reduced in cases of demander idle waiting for the next messages from the supplier