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- num-immutable-mem-table
- cur-size-active-mem-table
- cur-size-all-mem-tables
- size-all-mem-tables
- num-entries-active-mem-table
- num-entries-imm-mem-tables
- num-deletes-active-mem-table
- num-deletes-imm-mem-tables
- mem-table-flush-pending
- num-running-flushes
- compaction-pending
- num-running-compactions
- estimate-pending-compaction-bytes
- total-sst-files-size
- live-sst-files-size
- num-live-versions
- block-cache-capacity
- block-cache-usage
- block-cache-pinned-usage
- estimate-num-keys
- estimate-table-readers-mem
- estimate-oldest-key-time
- background-errors
The recording level for all metrics will be INFO
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Estimated memory in bytes used for reading SST tables, excluding memory used in block cache (e.g., filter and index blocks). This metric records the memory used by iterators as well as filters and indices if the filters and indices are not maintained in the block cache. Basically this metric reports the memory used outside the block cache to read data. For segmented state stores, the sum of the estimated memory over all segments is reported.
estimate-oldest-key-time
background-errors
Accumulated number of background errors. Estimated oldest key timestamp in the RocksDB instance. This metric is currently only available for FIFO compaction with compaction_options_fifo.allow_compaction = false. For segmented state stores, the minimum sum of the estimated oldest key timestamp number of background errors over all segments is reported.
background-errors
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Examples
- If users want to monitor the total memory usage of RocksDB, they should compute size-all-mem-tables + block-cache-usage + estimate-table-readers-mem. All of this memory is off-heap memory, i.e., it is not managed by the JVM. Note, that the monitored total memory usage is an estimation. Users can bound the total memory usage by configuring RocksDB as described in https://kafka.apache.org/25/documentation/streams/developer-guide/memory-mgmt.html#rocksdb
- With mem-table-flush-pending and num-running-flushes, users can monitor the flushing behavior of their state stores. Similarly, users can monitor the compaction behavior of their state stores with compaction-pending and num-running-compactions.
- To monitor the sizes of the LSM trees used in their state stores, users can monitor total-sst-files-size.
Performance Consideration
All the metrics will be implemented as gauges. That means, the metrics would not be recorded if the metrics reporting system used by the user does not query the metric. Hence, the number of metrics presented in this KIP should neither affect the performance of the RocksDB instances nor the performance of Kafka Streams if they are not queried.
Compatibility, Deprecation, and Migration Plan
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