1、使用異步算子,異步執(zhí)行操作
2、將下游數(shù)據(jù)需要的數(shù)據(jù)以參數(shù)的形式向下傳遞
3、當(dāng)服務(wù)器資源有限的情況下,慎用RocksDBStateBackend
RocksDBStateBackend performance will be poor because of the current Flink memory configuration! RocksDB will flush memtable constantly, causing high IO and CPU. Typically the easiest fix is to increase task manager managed memory size. If running locally, see the parameter taskmanager.memory.managed.size. Details: arenaBlockSize 8388608 > mutableLimit 3737299 (writeBufferSize = 67108864, arenaBlockSizeConfigured = 0, defaultArenaBlockSize = 8388608, writeBufferManagerCapacity = 4271199)文章來源:http://www.zghlxwxcb.cn/news/detail-623457.html
明確指出,當(dāng)前內(nèi)存有限的情況下,使用rocketDB會造成性能損害,因為rocketDB會不停刷內(nèi)存,造成高io和高cpu。所以在小型化項目時,對狀態(tài)數(shù)據(jù)要求不高時,可考慮不使用rocketDB作為狀態(tài)后端文章來源地址http://www.zghlxwxcb.cn/news/detail-623457.html
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