Migrate data with Spark to Elasticsearch – What you need to know

Migrating your data can be a challenging process, however, it can become a necessity. Organisations will migrate their data from one solution to another for multiple reasons including to reduce costs, improve performance or gain better flexibility. In this article, we will look at migrating data with Spark to Elasticsearch and if this is something you should consider for your data.

What is Spark?

Apache Spark is one of the leading data processing technologies employed to process large sets of data with speed and efficiency. It can be used as a part of data infrastructure within AWS, Google, Microsoft Azure and Databricks technologies. Apache Spark is used by some of the leading brands in the world including the likes of Apple, Facebook and Netflix.

Benefits of Spark

There are several benefits of using Spark and they include:

• The high processing speed of data – Especially when compared to other popular data processing technologies such as Hadoop, it is 100% faster.
• Easy to use – With over 80 APIs at hand, it is generally considered easy to use
• Advanced analytics – With these capabilities, it empowers organisations to drive data analysis and reporting
• Multiple programming languages – You can employ multiple programming languages including Python, Java, Scala and more.
• Open source – Spark is an open-source technology which has a great community that can help provide, support and assistance if required.

Limitations of Spark

There are some limitations of Spark which you need to consider and they include:

• Lack of automation – With many other technologies moving towards automation, Spark is yet to move toward code optimisation.
• File management – File management has to be carried out with other technologies as they are not provided with Spark.
• Steep learning curve – Although it is considered easy to use, there is a step learning curve to getting to grips with it.

What is Elasticsearch?

Elasticsearch is essentially a Database Management System that enables you to store, search and carry out analysis of large volumes of data quickly and efficiently. Elasticsearch has developed over time and has become of the leading technologies for data analysis and visualisation to drive Business Intelligence for organisations around the world. Some of the biggest brands that use Elasticsearch include Shopify, Uber and Slack.

Benefits of Elasticsearch

The benefits on offer with Elasticsearch include:

• Platform compatibility – It can run on almost any platform as it is developed in Java
• High speeds – Near real-time data speeds can be achieved with the data search
• Highly scalable – Due to its distributed document orientated, it can be easily scaled up
• Open source – As it is an open-source technology there are no licensing fees associated with it, making it a cost-effective solution.

Limitations of Elasticsearch

Some limitations of Elasticsearch to consider are:

• Learning curve – Although it has multiple benefits it does require expert skills to use the technology effectively.
• Hardware requirement – As you scale up, you may require hardware in order for the technology to perform at its peak potential which can be costly.

Migrating your data to Elasticsearch with Spark

When migrating data to Elasticseach data engineers will have to choose the right stack for the job. One of the most commonly used technologies is Spark. As discussed, Spark is a powerful technology which can be leveraged for data migration between Elasticsearch clusters.

How to ensure a successful migration

There are a number of factors to consider when it comes to successful data migration and they include:

• Outline goals and objective
• Choosing the right data migration strategies
• Selecting the right data migration technology
• Creating a detailed risk assessment
• Creating and communicating the budget
• Establishing a project timeline
• Robust testing measure

Read the full plan on how to plan your data migration.

Ardent data migration services

Ardent has delivered a wide variety of data migration solutions for multiple clients over the last decade. With a vast majority of data migrations doomed to fail, our expert engineers have established a robust process to ensure your data migration is carried out successfully within time and budget. If you are looking to migrate your data from Spark to Elasticsearch or from one cloud solution to another, we can help. Explore our data engineering success stories:

• Intelligent platform to automate information security using Elasticsearch
• Robust, scalable data pipelines with AWS infrastructure
• Managing and optimising 4 petabytes of client data

 Get in touch to find out more to explore our data services.

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