Flink rocksdb memory leak. yaml is related to the runtime memory usage of taskmanager.
Flink rocksdb memory leak import Mar 8, 2022 · We found this useful for observing memory trends over longer periods of time, helping us detect memory leaks in RocksDB for one of our applications. fraction from 0. If neither this option, nor the 'state. See Improving Memory Efficiency. Mar 8, 2024 · Memory growth 1mb per second until the process crashes, as if the state value stays in memory. For some ongoing projects that improve memory efficiency. On Windows or macOS it grows and grows and grows so much that after a few days it's like 7-9 GB consumption and growing. RocksDB itself needs native memory which adds to Flink's memory footprint. 10 comes with significant changes to the memory model of the Task Managers and configuration options for your Flink applications. Configure memory for standalone deployment # It is recommended to configure total Flink memory (taskmanager. Nothing else is Mar 8, 2024 · Memory growth 1mb per second until the process crashes, as if the state value stays in memory. If I have more insight about memory consumption or leaks I will open a new ticket. Oct 6, 2024 · I have a Java app running on AWS Flink version 1. If you give RocksDB rather less memory, it should cope. This relates to memory managed by Flink outside the Java heap. Jul 26, 2020 · increase RocksDB blockcache size(e. Either there is a memory leak, or my setup with default RocksDB configuration just doesn't fit the example. 9, it's not surprising that your overall memory usage approaches its limit over time. when the RocksDB blockcache reachs maximum size, restart the job. 15. and memory will keep raising. Reload to refresh your session. In this post, we describe Flink’s memory model, as it stands in Before FLINK-12785, user may encounter OOM if there are huge KV pairs when restoring from savepoint of RocksDB state backend. To control memory manually, you can set state. 1G), it is easier to monitor and reproduce. The root cause is the memory fragmentation with glibc. Sep 29, 2023 · Figure 1: Flink’s memory model. The app aggregates numbers in a keyed stream over 1-minute windows. Rest of app is tight. createLocalEnvironment and creating a simple Flink job and setting the parallelism "high enough". Feb 4, 2022 · RocksDB is designed to use all of the memory you give it access to -- so if it can fit all of your state in memory, it will. I will observe it. fixed-per-slot or state. fixed-per-tm options). You signed out in another tab or window. This is due to the unfortunate fact that even with the RocksDB upgrade of Flink 1. These recently-introduced changes make Flink more adaptable to all kinds of deployment environments (e. 0 as it has lots of shiny stuff that fits our use-case exactly (RocksDB state backend running in a containerised cluster). You may get some information in FLINK-18712[1]. backend. import Jul 21, 2018 · But on macOS and on Windows it leaks memory. Even though Flink’s RocksDB state backend is operating off-heap, you should still keep an eye out on memory and GC. We are getting this error: This option overrides the 'state. This depends on the block cache size, indexes, bloom filters and memtables. 截至当前，Flink作业的状态后端仍然只有Memory、FileSystem和RocksDB三种可选，且RocksDB是状态数据量较大（GB到TB级别）时的唯一选择。RocksDB的性能发挥非常仰赖调优，如果全部采用默认配置，读写性能有可能会很差。 Memory tuning guide # In addition to the main memory setup guide, this section explains how to set up memory depending on the use case and which options are important for each case. 20. 14 (to RocksDB 6. As seen in Figure 1, Flink’s direct memory configuration can be split into three parts — framework off-heap, task off-heap and network memory. And given that you've increased taskmanager. managedMemoryTotal* Bytes: The total amount of managed memory. start a job using RocksDB statebackend. If there is a leak, then it is likely in RocksDB (native memory) and not the (Java) application on top of it, as the Java heap is limited. managed. 13 only. Hi Fabian, Thanks for collecting feedback. 4 to 0. flink. state. 10, Flink configures RocksDB’s memory allocation to the amount of managed memory of each task slot by default. Yes, we enabled incremental checkpoints for our job by setting `state. Kubernetes, Yarn, Mesos), providing strict control over its memory consumption. go through step 2-3 few more times. 1: Double Flink RocksDB状态后端参数调优实践 Foreword. Unfortunately, it seems like there is a memory leak somewhere in the job submission logic. backend restore:从状态中恢复RocksDB的Snapshot，主要包含对应的RocksDB实例、列族处理器、RocksDB指标采集器、SST文件、最后依次的ck id(具体查看RocksDBRestoreResult对象)。 RocksDBRestoreOperation:主要的RocksDB状态恢复操作接口，提供了增量恢复、全量快照恢复、不恢复等策略。 Mar 23, 2022 · 关于RocksDB使用托管内存，Flink官方文档给出了一段简短的解释： Flink does not directly manage RocksDB’s native memory allocations, but configures RocksDB in a certain way to ensure it uses exactly as much memory as Flink has for its managed memory budget. Alternatively, you can use the above mentioned cache/buffer-manager mechanism, but set the memory size to a fixed amount independent of Flink’s managed memory size (state. Application, Operator, Task, Parallelism *Available for Managed Service for Apache Flink applications running Flink version 1. Please note here that the options below are not exhaustive since you can manage the state size of your Flink application with the State TTL (Time-To-Live Simulate Flink RocksDB Memory Leak Issue in >=1. I am now closing this ticket, as the first aspect ("swap usage") is not a RocksDB issue. I'm pretty sure the leak is inside rocksdb. Here's the answers to your questions: 1. Feb 26, 2020 · Now that we established RocksDB’s functionality with Apache Flink, let’s have a look at the configuration options that can help you manage your RocksDB memory size more effectively. size) or its components for standalone deployment where you Nov 21, 2023 · I also set the Managed Memory to 0 since I'm not using RocksDB as state backend, so the intermediate states should be stored on the heap memory. and monitor the memory usage (k8s pod working set) of the TM. Data is received from Kinesis input stream and sent over to Kinesis output s We've just tried deploying 1. managed' optionare set, then each RocksDB column family state has its own memory caches (as controlled by the column family options). yaml is related to the runtime memory usage of taskmanager. May 9, 2022 · You signed in with another tab or window. I've also tested `MapState`, it's the same. Memory tuning guide # In addition to the main memory setup guide, this section explains how to set up memory depending on the use case and which options are important for each case. Actually there are some efforts from the Flink side, such as using jemalloc as default in image[2]. (I do not care about Savepoints and Checkpoint mechanism about in flink, I am just creating state which almost 5 mins ttl) However memory consumption for all nodes are always increasing and I have to do stop flink application via stop-cluster. 3), while doing its best, Flink is not able to fully control how . Any solution or suggestion for Hi Sue Alen, AFAIK, Flink encountered memory leak issues with RocksDB block cache. On Linux memory usage is rock solid at 800- 900MB even if the process is up for a month. User could tune the limit through the state. It is used for the RocksDB state backend, and is also available to applications. Eclipse Memory Analyzer (Eclipse MAT) : Eclipse MAT is a Java heap analyzer used to inspect JVM heap dumps for memory utilization, finding memory leaks, etc. ```python import time. There are a couple of components in RocksDB that contribute to memory usage: Block cache; Indexes and bloom filters; Memtables; Blocks pinned by iterators; We will describe each of them in turn. sh, then re-start again. high-prio-pool-ratio: 0. Sep 15, 2020 · Use RocksDB state backend; Use managed memory; have "low" managed memory size; have "high" parallelism (e. g. You switched accounts on another tab or window. fraction. 5) OR have enough operators (the exact count unknown) The easiest way to do all this is to do StreamExecutionEnvironment. rocksdb. Jan 18, 2021 · Since Flink 1. In FLINK-12785 we introduce a size limit in RocksDBWriteBatchWrapper with default value 2MB, and RocksDB's WriteBatch will flush if the consumed memory exceeds it. size or taskmanager. managed to false and configure RocksDB via ColumnFamilyOptions. Apr 16, 2021 · Also I am using rocksdb as state management. size) or its components for standalone deployment where you Jun 12, 2018 · If this is the case, then you should try to refactor your code to rely on Flink's state abstraction, because with RocksDB it can go out of core. 11 - qqibrow/flinkmemoryleak Here we try to explain how RocksDB uses memory. This is done on a per-slot level (managed memory is accounted per May 31, 2022 · Flink troubleshooting: TaskManager memory and GC details. For example, by default it's set to 256MB, when a job is Apr 21, 2020 · Apache Flink 1. size or jobmanager. I found an interesting thing here: the size of Task Heap configured in flink-conf. The primary mechanism for improving memory-related performance issues is to increase Flink’s managed memory via the Flink configuration taskmanager. memory. For example, by default it's set to 256MB, when a job is Memory tuning guide # In addition to the main memory setup guide, this section explains how to set up memory depending on the use case and which options are important for each case. managed' option when configured. incremental` to true. Same thing happens if I send 100 messages per second with 10kb each. 10. aepdf wqfqia diwps keskvmva evxcnz lfdnny wbp srjtw csq gijbfw