Evaluate and run Hadoop in the GoGrid Cloud

Hadoop Big Data Solution

Evaluate, develop, test, deploy, and scale Hadoop clusters on GoGrid quickly and easily.

  • Deploy Hadoop on either Dedicated Servers or Cloud Servers
  • Deploy Hadoop with HBase using 1-Button Deploy™ technology
  • Purpose-built infrastructure ensures reliable performance


Hadoop is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. GoGrid has made the deployment of Hadoop with HBase clusters easy with 1-Button Deploy™ technology. Customers can deploy Hadoop with HBase as a developer environment or a production environment.

Customers can also manually deploy Hadoop by itself on our high-performance Cloud Servers using the recommended configuration (below) or on purpose-built Dedicated Servers. The following examples are recommended infrastructure for either a development or production environment.

Product Infrastructure Hourly
Development Environment

Any Hadoop Open Source Distribution

  • 3 Data Nodes – Large Raw Disk Cloud Servers
  • 1 Name Node – Medium SSD Cloud Server
Production Environment

Any Hadoop Open Source Distribution

  • 5 Data Nodes – X-Large Raw Disk Cloud Servers
  • 2 Name Nodes – X-Large SSD Cloud Servers

Dedicated Servers

In addition to 1-Button-Deploy™, customers can also elect to deploy GoGrid Dedicated Servers that are designed to work specifically with Hadoop. We’ve worked closely with our partners on these specifications so they’ll match most Hadoop use cases. The Data Node uses a JBOD (Just a Bunch of Disks) configuration and should be deployed with other Data Nodes to ensure data replication (for a small cluster, use at least 3 Data Nodes). Order the following servers from Sales or customize base Dedicated Servers to fit your needs.

GoGrid Hadoop Dedicated Servers
Product Name Node Data Node
Monthly $700 $700
Annual $7,000 $7,000
Storage 4 x 1 TB SATA RAID 1 4 x 2 TB SATA JBOD
RAM 48 GB 24 GB
Cores 12 12

Use Cases

How you structure your app to run should take into account the unique needs of your application, including access patterns such as read-write distribution and latency differences between various operations. The examples listed here aren’t necessarily right for your application, but illustrate some common approaches to thinking about and implementing the solution.

Use Case for Hadoop as a Big Data Solution in the GoGrid Cloud

  • Clickstream analysis – Often used to understand how website visitors make purchase decisions, clickstream data storage and analysis allows marketers to create unique user experiences on a variety of levels. Leveraging Hadoop and either Cassandra or HBase, users can create data hubs and leverage Hadoop’s unique toolset to do things like join that data to other data sources.
  • Sentiment data – With Hadoop, users can load social media posts into the Hadoop Distributed File System (HDFS) using Apache Flume for real-time streaming. Apache Pig and Apache Mahout organize the unstructured data for scoring. After scoring sentiment, data can be joined with other sources of data for use in applications.
  • Sensor data & log file data – The two most common use cases for server log data are network security breaches and network compliance audits. Users can then sort this data to perform forensic analysis. Leveraging Hadoop, administrators have a toolset for establishing recurring processes to flag data abnormalities and send alerts to applications or log abnormalities in standardized reports.
  • Predictive analytics – With Hadoop, users can identify and explore data patterns. Using tools like Apache Hive and Apache Pig, users can then join data sets with additional sources and separate out important predictive indicators.

For predictive analytics, distributed processing of large data sets, clickstream analysis, or managing sentiment, sensor, and log file data.


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