Alluxio, the developer of open source data orchestration software for the cloud, has announced the immediate availability of version 2.8 of its Data Orchestration Platform. Featuring enhanced interface support for the Amazon S3 REST API, the latest release bundles security improvements for sensitive applications with strict encryption compliance and regulatory requirements.
COMMUNITY VIRTUAL EVENT
Learn how Alluxio uses Apache Ranger’s centralized access policies to control access to virtual paths in the Alluxio virtual file system and enforce existing access policies for the HDFS under stores.
Check out the talks from our virtual community event, Alluxio Day XII, featuring presenters from Websec, Shopee, and Alluxio.
Alluxio 2.8 expands data access & security for data-driven applications in heterogeneous environments – Enhanced S3 API, data encryption & policy-driven data management, and more.
Alluxio enables compute
Bring your data close to compute.
Make your data local to compute workloads for Spark caching, Presto caching, Hive caching and more.
Make your data accessible.
No matter if it sits on-prem or in the cloud, HDFS or S3, make your files and objects accessible in many different ways.
Make your data as elastic as compute.
Effortlessly orchestrate your data for compute in any cloud, even if data is spread across multiple clouds.
“zero-copy” burst user spotlight: walmart
Why Walmart chose Alluxio’s “Zero-Copy” burst solution:
- No requirement to persist data into the cloud
- Improved query performance and no network hops on recurrent queries
- Lower costs without the need for creating data copies
Featured Use Cases and Deployments
Zero-copy hybrid bursting with no app changes to intelligently make remote data accessible in the public cloud.
Zero-copy bursting across data centers for Presto, Spark, and Hive with no app changes on data stored in HDFS.
Interact with Alluxio in any stack
Pick a compute. Pick a storage. Alluxio just works.
// Using Alluxio as input and output for RDD scala> sc.textFile("alluxio://master:19998/Input") scala> rdd.saveAsTextFile("alluxio://master:19998/Output") // Using Alluxio as input and output for Dataframe scala> df = sqlContext.read.parquet("alluxio://master:19998/Input.parquet") scala> df.write.parquet("alluxio://master:19998/Output.parquet”)
-- Pointing Table location to Alluxio hive> CREATE TABLE u_user ( userid INT, age INT) ROW FORMAT DELIMITED FIELDS TERMINATED BY '|' LOCATION 'alluxio://master:port/table_data';
Create and Query table stored in Alluxio hbase(main):001:0> create 'test', 'cf' hbase(main):002:0> list ‘test'
# Accessing Alluxio after mounting Alluxio service to local file system $ ls /mnt/alluxio_mount $ cat /mnt/alluxio_mount/mydata.txt
powered by alluxio
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