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Available on Google Cloud Marketplace and powered by Miri infotech, Cassandra offers robust support for clusters spanning multiple datacenters. It is highly scalable and great in performance. Cassandra has peer to peer distributed system across its nodes where data is distributed among all the nodes in a cluster. Each and every node is independent as well interconnected to the other nodes.

Miri Infotech, a leading IT solutions provider is launching a product that will configure and publish Cassandra, to produce free implementations of distributed or otherwise scalable and high availability which is embedded pre-configured tool with Ubuntu and ready-to-launch Machine Image on Google Cloud that contains Cassandra and Hadoop.

One of the things about Cassandra that users enjoy is that there is no single point of failure in its database and no network bottlenecks. Apache Cassandra is not just limited to this but is also a NoSQL(Not Only Sql) database management system that is designed to handle large amounts of data across numerous commodity servers. Cassandra’s level of performance is also high which makes it more impactful as well as flexible that can to be easily used by everyone.

It uses the concept of nodes where there is no master node but instead all the nodes play undistinguishable role and communicates with each other equally. The key components of Cassandra are−

Bloom filter − Quick, nondeterministic, algorithms for testing whether an element is a member of a set. Bloom filters can be accessed after every query. It is a special kind of cache.
Data center − It is a group of related nodes.
Commit log − The commit log is a crash-recovery mechanism and every write operation is written to the commit log.
Node − It is the place where data is stored.
Cluster − A cluster contains one or more data centers.
Mem-table − Mem-table is a memory-resident data structure. After commit log, the data will be written to the mem-table.
SSTable − It is a disk file to which the data is flushed from the mem-table when its contents reach the threshold value.

Usage / Deployment Instructions

Step 1: Access the Cassandra in Google Marketplace and click the LAUNCH ON COMPUTE ENGINE button.

Step 2: In the Configure & Deploy window, enter or select appropriate values for zone, machine type, and so on. Click the Deploy button.

Step 3: The Google Developers Console confirms that Cassandra was deployed

To access the application:

Step 1: SSH into the machine and follow the below instructions.

Step 2: Please run the following command:

sudo su
echo "127.0.0.1 `hostname`" >> /etc/hosts

Step 3: Use following Linux command to start cassandra

Note: Please do not copy the below commands, type it manually.

Command- cassandra -R

Now, please press Ctrl+C to exit from the running command.

Step 4: Type the command- cqlsh

Run any cassandra command and enjoy.

Note: you can type quit to exit from the ongoing Cassandra cluster.

All your queries are important to us. Please feel free to connect.

24X7 support provided for all the customers.

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Submit your Query: http://www.miritech.com/ContactUs.aspx

Contact Numbers:

(510) 298-5936
(510) 870-8668

Contact E-mail:

support@miritech.com

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You can subscribe to this product from GCP Marketplace and launch an instance from the product's image using the GCP compute service.

Go to the VM instances page.
Select your project and click Continue.
Click the Create instance button.
Specify a Name for your instance.
Optionally, change the Zone for this instance.

Note: The list of zones is randomized within each region to encourage use across multiple zones.

Select a Machine configuration for your instance.
In the Boot disk section, click Change to configure your boot disk.

Create a boot disk no larger than 2 TB to account for the limitations of MBR partitions.

Select the Custom Images tab.
Select the image project from the dropdown.
Choose the image you want and click the Select button.
To permit HTTP or HTTPS traffic to the VM instance, select Allow HTTP traffic or Allow HTTPS traffic.

The GCP Console adds a network tag to your instance and creates the corresponding ingress firewall rule that allows all incoming traffic on tcp:80 (HTTP) or tcp:443 (HTTPS). The network tag associates the firewall rule with the instance. For more information, see Firewall Rules Overview in the Virtual Private Cloud documentation.

To add secondary non-boot disks to your VM instance:
1. Click Management, security, disks, networking, sole tenancy.
2. Select the Disks tab.
3. Under Additional disks click Add new disk.
4. Specify a disk Name, Type, Source type, Mode, and Deletion rule.
5. Click Done.
6. Add additional disks as needed.
Click the Create button to create and start the instance.

1What is Hadoop?

The Apache Hadoop software library allows for the distributed processing of large data sets across clusters of computers using a simple programming model. The software library is designed to scale from single servers to thousands of machines; each server using local computation and storage. Instead of relying on hardware to deliver high-availability, the library itself handles failures at the application layer. As a result, the impact of failures is minimized by delivering a highly-available service on top of a cluster of computers.
2Where does Hadoop find applicability in business?

Hadoop, as a scalable system for parallel data processing, is useful for analyzing large data sets. Examples are search algorithms, market risk analysis, data mining on online retail data, and analytics on user behavior data.
3What is big data security analytics?

Add the words “information security” (or “cybersecurity” if you like) before the term “data sets” in the definition above. Security and IT operations tools spit out an avalanche of data like logs, events, packets, flow data, asset data, configuration data, and assortment of other things on a daily basis. Security professionals need to be able to access and analyze this data in real-time in order to mitigate risk, detect incidents, and respond to breaches. These tasks have come to the point where they are “difficult to process using on-hand data management tools or traditional (security) data processing applications.”
4Is there an easy way to migrate data from Hadoop into a relational database?

The Hadoop JDBC driver can be used to pull data out of Hadoop and then use the DataDirect JDBC Driver to bulk load the data into Oracle, DB2, SQL Server, Sybase, and other relational databases.
5What are the popular machine learning algorithms in use today?
There are many machine learning algorithms in use today, but the most popular ones are:
- Decision Trees
- Naive Bayes Classification
- Ordinary Least Squares Regression
- Logistic Regression
- Support vector machines
- Ensemble Methods
- Clustering Algorithms
- Principal Component Analysis
- Singular Value Decomposition
- Independent Component Analysis

Cassandra

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1What is Hadoop?

2Where does Hadoop find applicability in business?

3What is big data security analytics?

4Is there an easy way to migrate data from Hadoop into a relational database?

5What are the popular machine learning algorithms in use today?

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