What's New In Apache Ozone 1.3系统均衡器(Container Balancer) III. 性能优化 - ⽂件系统优化(File System Optimization) IV. 性能优化 - 合并Container RocksDB实例 V. 很多其他的性能和稳定性优化 6 纠删码 数据可靠性 (越⾼越好) 存储效率 (越⾼越好) 1-replica 0 100% 3-replica 2 33% EC RS(6 只迁移CLOSE状态的Container VII.客户端发送命令给SCM,SCM负责 执⾏和控制整个流程 Ozone Manager DN1 Storage Container Manager Client RocksDB RocksDB C3 C4 C5 C6 C2 C1 C1 C2 C3 C4 C5 C6 C1 C2 C3 C4 C5 C6 DN2 DN3 DN4 C2 C4 C6 C5 发送命令 delete(“/catelog_sales”) 18 合并Container RocksDB实例 - 现状和问题 每个Container有独⽴的RocksDB实例保存元数据(V2) 问题 I. ⼤容量磁盘,系统中有上万个Container和RocksDB实例 II. 内存开销⼤,需保留众多RocksDB实例 III. 性能影响,频繁create/open/close实例 IV. 磁盘使⽤量,不可精准预测 0 码力 | 24 页 | 2.41 MB | 1 年前3
2022 Apache Ozone 的最近进展和实践分享OM – 管理Ozone的Namespace ,也使⽤了RocksDB 2. SCM – 管理Ozone集群和数据 3. Recon Server – 监控Ozone集群 4. DataNode – 负责存储和汇报Storage Containers 5. Storage Containers – Ozone的存储单元,内置有RocksDB 数据库 Apache Ozone – 数据访问的API Ozone适⽤场景 • Apache Ozone的最近进展 • Apache Ozone的实践分享 新进展 • ⽂件系统优化(FSO) • Ozone Balancer • 纠删码 • 单数据盘单RocksDB实例 ⽂件系统优化(FSO) dir1 dir2 dir3 file-1 file-1M 100万个⽂件 vol/buck1 Key entry /vol/buck1/dir1/ 只迁移CLOSE状态的Container ● 客户端发送命令给SCM,SCM负 责执⾏和控制流程 Ozone Manager DN1 Storage Container Manager Client RocksDB RocksDB C3 C4 C5 C6 C2 C1 C1 C2 C3 C4 C5 C6 C1 C2 C3 C4 C5 C6 DN2 DN3 DN4 C2 C4 C6 C5 发送命令0 码力 | 35 页 | 2.57 MB | 1 年前3
Ozone meetup Nov 10, 2022 Ozone User Group Summitof replication (collection of blocks) ● RocksDB - container metadata • Supported by and battle-tested at Facebook. • OM – a namespace manager (also uses RocksDB to store the namespace) • HDDS – a distributed reserved. FSO BUCKET IMPLEMENTATION • Implement a hierarchical layout with a key value store (RocksDB) – Key:/ 0 码力 | 78 页 | 6.87 MB | 1 年前3
State management - CS 591 K1: Data Stream Processing and Analytics Spring 2020filesystem or a database system • Available state backends in Flink: • In-memory • File system • RocksDB State backends 7 Vasiliki Kalavri | Boston University 2020 MemoryStateBackend • Stores state Vasiliki Kalavri | Boston University 2020 RocksDBStateBackend • Stores all state into embedded RocksDB instances • Accesses require de/serialization • Checkpoints state to a remote file system and supports Kalavri | Boston University 2020 RocksDB 10 RocksDB is an LSM-tree storage engine with key/value interface, where keys and values are arbitrary byte streams. https://rocksdb.org/ https://www.ververica0 码力 | 24 页 | 914.13 KB | 1 年前3
Performance of Apache Ozone on NVMedestaged to disk • OM uses NVME to store RocksDBs • Future projects such as Snapshots leverage RocksDB to preserve simplicity of IO path. Ozone scales! Does background scale up and scale out? • Datanode DataNode) Lesson Learned Too many rocksdb instances is bad One RocksDB to manage the metadata of a 5GB container But a DataNode can be up to a few hundred TB → 100k rocksdb instances. Very slow to load (HDDS-3892, HDDS-4427, HDDS-4488, HDDS-5785) Error prone (HDDS-5756/rocksdb issue:8617) → HDDS-3630 (Merge rocksdb in datanode) ● One rocksdb instance to manage the containers of a disk Write path improvements0 码力 | 34 页 | 2.21 MB | 1 年前3
监控Apache Flink应用程序(入门)e-1.7/ops/config.html#configuring-the-network-buffers 8 https://www.da-platform.com/blog/manage-rocksdb-memory-size-apache-flink? __hstc=216506377.c9dc814ddd168ffc714fc8d2bf20623f. 1550652804788.1550652804788 particularly important, when using the RocksDB statebackend, since RocksDB allocates a considerable amount of memory off heap. To understand how much memory RocksDB might use, you can checkout this blog0 码力 | 23 页 | 148.62 KB | 1 年前3
Streaming in Apache Flinkautomatically checkpointed and restored • vertically scalable: Flink state can be kept in embedded RocksDB instances that scale by adding more local disk • horizontally scalable: Flink state is redistributed0 码力 | 45 页 | 3.00 MB | 1 年前3
Graph streaming algorithms - CS 591 K1: Data Stream Processing and Analytics Spring 2020• How to represent the spanner? As an adjacency list? which state primitives are suitable? Is RocksDB a suitable backend for graph state? • How to compute the distance between edges? Do we need to0 码力 | 72 页 | 7.77 MB | 1 年前3
Exactly-once fault-tolerance in Apache Flink - CS 591 K1: Data Stream Processing and Analytics Spring 2020to checkpoint? Do we need to checkpoint the complete application state in every checkpoint? • RocksDB supports both asynchronous and incremental checkpoints: • take a local snapshot and use a background0 码力 | 81 页 | 13.18 MB | 1 年前3
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