![]() ![]() Once a file is written and closed, it is guaranteed to view the written data in the following open and read. root/soft/pjdfstest/tests/chown/00.t (Wstat: 0 Tests: 1323 Failed: 0) JuiceFS has passed all of the compatibility tests (8813 in total) in the latest pjdfstest. Please refer to JuiceFS Document Center for more information. If you wanna use JuiceFS in Hadoop, check Hadoop Java SDK. ![]() It is also very easy to use JuiceFS on Kubernetes. JuiceFS can be used as a persistent volume for Docker and Podman, please check here for details. Please refer to Quick Start Guide to start using JuiceFS right away! Command ReferenceĬheck out all the command line options in command reference. JuiceFS Client downloaded and installed.Don't panic! This is just the secret of the high-performance operation of JuiceFS! Getting Started Therefore, the source files stored in JuiceFS cannot be found in the file browser of the object storage platform instead, there are only a chunks directory and a bunch of digitally numbered directories and files in the bucket. When using JuiceFS, files will eventually be split into Chunks, Slices and Blocks and stored in object storage. These blocks will be stored in object storage in the end at the same time, the metadata information of the file and its Chunks, Slices, and Blocks will be stored in metadata engines via JuiceFS. Each slice is composed of size-fixed "Block" s, which are 4 MiB by default. Each Chunk is composed of one or more "Slice"(s), and the length of the slice varies depending on how the file is written. Learn moreĮach file stored in JuiceFS is split into "Chunk" s at a fixed size with the default upper limit of 64 MiB. JuiceFS can store the metadata of file system on Redis, which is a fast, open-source, in-memory key-value data storage, particularly suitable for storing metadata meanwhile, all the data will be stored in object storage through JuiceFS client. Metadata Engine: Stores the corresponding metadata that contains information of file name, file size, permission group, creation and modification time and directory structure, etc., with supports of different metadata engines, e.g., Redis, MySQL, SQLite and TiKV.Data Storage: Stores data, with supports of a variety of data storage media, e.g., local disk, public or private cloud object storage, and HDFS.JuiceFS Client: Coordinates object storage and metadata storage engine as well as implementation of file system interfaces such as POSIX, Hadoop, Kubernetes, and S3 gateway.Data Compression: JuiceFS supports LZ4 or Zstandard to compress all your data.Īrchitecture | Getting Started | Advanced Topics | POSIX Compatibility | Performance Benchmark | Supported Object Storage | Who is using | Roadmap | Reporting Issues | Contributing | Community | Usage Tracking | License | Credits | FAQ.Global File Locks: JuiceFS supports both BSD locks (flock) and POSIX record locks (fcntl).Data Encryption: Supports data encryption in transit and at rest (please refer to the guide for more information).Outstanding Performance: The latency can be as low as a few milliseconds, and the throughput can be expanded nearly unlimitedly (depending on the size of the object storage).Strong Consistency: The confirmed modification will be immediately visible on all the servers mounted with the same file system.Shareable: JuiceFS is a shared file storage that can be read and written by thousands of clients.Cloud Native: A Kubernetes CSI Driver is provided for easily using JuiceFS in Kubernetes.S3-compatible: JuiceFS' S3 Gateway provides an S3-compatible interface.Fully Hadoop-compatible: JuiceFS' Hadoop Java SDK is compatible with Hadoop 2.x and Hadoop 3.x as well as a variety of components in the Hadoop ecosystems.Fully POSIX-compatible: Use as a local file system, seamlessly docking with existing applications without breaking business workflow.□ Document: Quick Start Guide Highlighted Features Without modifying code, the massive cloud storage can be used as efficiently as local storage. With JuiceFS, massive cloud storage can be directly connected to big data, machine learning, artificial intelligence, and various application platforms in production environments. Amazon S3), and the corresponding metadata can be persisted in various database engines such as Redis, MySQL, and TiKV based on the scenarios and requirements. The data, stored via JuiceFS, will be persisted in object storage (e.g. JuiceFS is a high-performance POSIX file system released under Apache License 2.0, particularly designed for the cloud-native environment. ![]()
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