Product School

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.

Watch on-demand >

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.

Read the blog >

We’re hiring! Join our team and build the future of data orchestration. See open positions >

Alluxio enables compute

Data locality

Bring your data close to compute.
Make your data local to compute workloads for Spark caching, Presto caching, Hive caching and more.

Data Accessibility

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.

Data On-Demand

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

See more on how Alluxio powers Walmart’s “zero-copy” burst solution in their presentation >

Featured Use Cases and Deployments

Managing data copies/app changes when bursting compute to cloud?

Zero-copy hybrid bursting with no app changes to intelligently make remote data accessible in the public cloud.

Expanding compute capacity across geo-distributed data centers?

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.

Tutorial –> Full Docs –>

-- Pointing Table location to Alluxio 
CREATE SCHEMA hive.web
WITH (location = 'alluxio://master:port/my-table/‘)

Full Docs

// 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”)

Full Docs

-- 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';

Full Docs

Create and Query table stored in Alluxio
hbase(main):001:0> create 'test', 'cf'
hbase(main):002:0> list ‘test'

Full Docs

# Running a wordcount using Alluxio as input and output
$ bin/hadoop jar hadoop-mapreduce-examples-2.7.3.jar wordcount \
  -libjars /<ALLUXIO_HOME>/client/alluxio-<VERSION>-client.jar \
  alluxio://master:19998/wordcount/input.txt \ 
  alluxio://master:19998/wordcount/output

Full Docs

# Accessing Alluxio after mounting Alluxio service to local file system
$ ls /mnt/alluxio_mount
$ cat /mnt/alluxio_mount/mydata.txt
ALLUXIO
$ ./bin/alluxio fs mount \
--option aws.accessKeyId=<AWS_ACCESS_KEY_ID> \
--option aws.secretKey=<AWS_SECRET_KEY_ID> \
alluxio://master:port/s3 s3a://<S3_BUCKET>/<S3_DIRECTORY>

Full Docs

$ ./bin/alluxio fs mount \
alluxio://master:port/hdfs hdfs://namenode:port/dir/

Full Docs

$ ./bin/alluxio fs mount \
--option
fs.azure.account.key.<AZURE_ACCOUNT>.blob.core.windows.net=<AZURE_ACCESS_KEY> \
alluxio://master:port/azure 
wasb://<AZURE_CONTAINER>@<AZURE_ACCOUNT>.blob.core.windows.net/<AZURE_DIRECTORY>/

Full Docs

$ ./bin/alluxio fs mount \
--option fs.gcs.accessKeyId=<GCS_ACCESS_KEY_ID> \
--option fs.gcs.secretAccessKey=<GCS_SECRET_ACCESS_KEY> \
alluxio://master:port/gcs gs://<GCS_BUCKET>/<GCS_DIRECTORY>

Full Docs

$ ./bin/alluxio fs mount \
--option aws.accessKeyId=<AWS_ACCESS_KEY_ID> \
--option aws.secretKey=<AWS_SECRET_KEY_ID> \
--option alluxio.underfs.s3.endpoint=http://<rgw-hostname>:<rgw-port> \
--option alluxio.underfs.s3.disable.dns.buckets=true \
alluxio://master:port/ceph s3a://<S3_BUCKET>/<S3_DIRECTORY>

Full Docs

$ ./bin/alluxio fs mount alluxio://master:port/nfs /mnt/nfs
 
 
 
 
 

Full Docs

powered by alluxio

What’s Happening

Event
Architecting a Heterogeneous Data Platform Across Clusters, Regions, and Clouds

Alluxio foresaw the need for agility when accessing data across silos separated from compute engines like Spark, Presto, Tensorflow and PyTorch. Embracing the separation of storage from compute, the Alluxio data orchestration platform simplifies adoption of the data lake and data mesh paradigm for analytics and AI/ML.

TDEA | Alluxio *
Press Release
Alluxio Will Present Session At Open Source Summit About Building Super-Contributors in an Open Source Community

SAN MATEO, CA – June 15, 2022 – Alluxio, the developer of the open source data orchestration platform for data driven workloads such as large-scale analytics and AI/ML, today announced it will present a session at the Linux Foundation’s Open Source Summit about strategies for building super-contributors in an open source community. The event is … Continued

News
DBTA 100 2022: The Companies That Matter Most in Data

Today, data-driven benefits abound. However, the ability to seize new business opportunities, create new products, and deal effectively with competitive issues requires strong data management and analytics capabilities.

DBTA

Blog
Modernize your analytics workloads with NetApp and Alluxio

Imagine as an IT leader having the flexibility to choose any services that are available in public cloud and on premises. And imagine being able to scale your storage for your data lakes with control over data locality and protection for your organization. With these goals in mind, NetApp and Alluxio are joining forces to help our customers adapt to new requirements for modernizing data architecture with low-touch operations for analytics, machine learning, and artificial intelligence workflows.