Release Notes

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We are excited to announce the release of Alluxio Enterprise Edition 2.0.0-1.0. This major release introduces new data management features, greatly improves usability and resolves several issues.

Versioning scheme: From Alluxio Enterprise Edition v2.0.0-1.0, the versioning scheme has been updated. The new versioning scheme appends a version suffix to the community version the release is based upon. For example, enterprise-v2.0.0-1.0 is based on the community version v2.0.0, with a version suffix of 1.0.

Compatibility: Alluxio 2 is not backward compatible with Alluxio 1; please see the documentation on how to upgrade from Alluxio 1 to Alluxio 2.

These are some of the highlights of the release.

Data Driven Applications

Native Support for AI & ML Workloads with Alluxio POSIX API

A POSIX compatible API has always been a highly requested feature, and the popularity of the API is second only to the Hadoop API. In Alluxio 2.0.0, we enable a POSIX compatible API through Alluxio FUSE. Alluxio can be mounted as a local file system volume and accessed through traditional POSIX compatible clients. This is especially useful for applications not originally built for big data but now require access to data which has been stored in a data lake, for example, machine learning using Tensorflow. See the docs for details.

Enable Better Performance for Object Store with Fast Commits

Compute frameworks which use rename to commit results run much slower on object storages due to rename being an expensive operation. Alluxio 2.0.0 enables users to write temporary data into Alluxio and then asynchronously persist the data to the underlying storage. See the docs for more details.


Support of Billions of Files with RocksDB Off Heap Metadata Management

Alluxio 2.0.0 provides the option to use RocksDB for storing file system metadata, enabling the namespace to scale to over one billion files. When running in off heap mode, an on-heap cache is used to serve more commonly accessed portions of the tree (for example, the root and top level directories), enabling most of the tree to be accessed at a similar speed as the in-memory metadata storage. Users can still configure alluxio.master.metastore=ROCKS to use the new RocksDB based metadata store.

Unified Data & Control Plane with gRPC

In Alluxio 2.0.0, we unify RPC framework for both control path and data path by replacing the Thrift/Netty based RPC framework with gRPC. Previously there were a lot of high level functions built on top of Netty to support high-performance data streaming, which is now much simplified with the built-in streaming APIs from gRPC. Code paths in Authentication, flow control and many other important features to support the legacy hybrid RPC framework are also unified on top of gRPC, which is much easier to maintain and extend from. All Alluxio RPC services are now defined using Protobuf IDL.

Ease of HA Deployment with RAFT based Embedded Journal

Alluxio 2.0.0 introduces a new mode for journaling metadata. The embedded journal is a fully contained, distributed state machine which uses the RAFT consensus algorithm. This allows users to have a fault tolerant and performant medium for journal storage, independent of 3rd party storage systems and zookeeper. Users running only on object stores will be able to deploy Alluxio in high availability mode without incurring a large metadata performance penalty or relying on another distributed storage. See the docs for more details.

Data Services

Alluxio 2.0.0 includes the Alluxio distributed Data Service, a set of services separate from the Alluxio masters and workers. The Alluxio Data Service acts as a lightweight distributed compute framework for internal Alluxio operations.

In this release, the following services are available:

Policy Driven Ufs Migration

Alluxio Enterprise Edition introduces UFS migration capabilities, defined by policies. Alluxio now supports mounting multiple UFS URI’s (sub-UFSes) to a single Alluxio mount point. Therefore, for all the Alluxio paths in this mount point, any single Alluxio URI is backed by more than one UFS path. Mounting multiple storage systems in Alluxio is enabled by the UnionUFS.

Once the UnionUFS is used for mounting, policies can be defined for UFS migration between the different sub-UFSes. A UFS migration policy defines an and a list of various operations, such as REMOVE and STORE. This policy means if a path is older than the , the following operations will be performed. For example, `ufsMigrate(2d, UFS[HDFS]:REMOVE, UFS[S3]:STORE)` is a policy definition which means “for all paths which are older than 2 days, the file will be stored in the S3 sub-UFS alias, and removed from the HDFS sub-UFS alias”. Alluxio’s internal policy engine continually enforces the policies on the paths. More details and examples can be found in the documentation for [UFS migration policies](advanced/Policy-Driven-Data-Management.html#moving-data-with-policies).

Active Replication

Users can set a min and max replication factor at the file level. The Data Service is used to enforce this by adding and removing copies in Alluxio storage. See the docs for more details.

Persist and Async Persist

The logic for writing a file synchronously or asynchronously to the under store is handled through the Data Service enabling better load balancing and error handling. See the docs for more details.

Cross Under Stores Data Move

Moving files and directories across mount points is now possible by using the Data Service to do the data transfer. See the docs for more details.

Distributed Load

The Data Service allows data to be evenly loaded across nodes. See the docs for more details.

Under Store

Active HDFS Under File System Sync

Alluxio 2.0.0 integrates with HDFS iNotify to update stale data and metadata in a subscription-based model instead of the on-demand polling which was previously done. This greatly reduces the period of time a stale read is possible and improves metadata performance by reducing the number of unnecessary calls to the backing store. See the docs for more details.

Web (HTTP & HTTPS) Under Store Support

Users can now bring in data even from web-based data sources to aggregate in Alluxio to perform their analytics. Any web location with files can be simplified pointed to Alluxio to be pulled in as needed based on the query or model run. See the docs for more details.


AWS Elastic Map Reduce (EMR) service integration

As users move to cloud services to deploy analytical and AI workloads, services like AWS EMR are increasingly used. Alluxio can now be seamlessly bootstrapped into an AWS EMR cluster making it available as a data layer within EMR for Spark, Presto and Hive frameworks. Users now have a high-performance alternative to cache data from S3 or remote data while also reducing data copies maintained in EMR. See the docs for more details.

Better Configuration Controls with Path Level Configuration

Users can specify default configuration on a per path basis, allowing administrators to have finer grained control on the settings clients use to access data. Clients may still override the path level configuration with client-side configuration. Path level configuration greatly simplifies the configuration necessary on client applications, for example, instead of having application logic switch write types, path level configuration can be used to ensure all writes to temporary directories are only written to memory. See the docs for more details.

Improved Kubernetes Deployment Support

Access Alluxio using the POSIX API from any application container in Kubernetes by simply mounting a hostPath volume after running the alluxio/alluxio-fuse container as a DaemonSet. See the docs for more details.

3rd Generation WebUI

The Alluxio web UI has been updated to use ReactJS and REST APIs. The overall user experience has been improved. The updated UI uses a dark theme with a better color palette. The set of cluster metrics and aggregated system metrics provided through the master has been improved. We have also added support for rendering timeseries on the UI. See the docs for more details.