In our age of technologies and the Internet, search engines have become powerful tools allowing for a variety of operations. Everyone applies these tools to find information on whatever topic they need. But, apart from being just a source of information, search engines can also bring many more advantages, especially the ones companies develop on their own.
In this article, you can find the steps that lead to the creation of a functional and efficient search engine software. First, let’s find out what this term means.
A search engine is web-based tool users utilize to find certain information on the Internet. Usually, it is an automated software application which can perform several functions:
Making your own search engine can be beneficial for a long-existing company as well as for startups because it helps to keep track of competition and gather important data and information about the customers.
If you are planning to build your own search engine, there are certain rules to follow.
There are two stages of the process and each has several steps.
This stage helps you prepare for developing your own engine software as well as explains how to launch it successfully.
First, you need to write down the requirements for the search. To understand this, you have to answer the following questions:
The second step of making your own search engine is to choose the engine itself. Exactly, there is no need to build a search engine software from scratch, you can select the existing one and tune it according to your needs. They are also very well optimized in terms of efficiency.
Solr, Elastic Search, Sphinx, Xapian are ones of the most popular. Let’s have a closer look at them.
It is open-source with refresh interval of 1 second which started in the early 2000s is financed by Elastic N.V. It helps customers explore and analyze different kinds of data like Apache logs and Twitter streams. It allows for the creation of the app, enterprise, and website search along with monitoring geo data, monitoring availability, and analyzing security events.
It is a dependable and scalable open-source enterprise search platform that provides load-balanced querying and replication, distributed indexing, automated failover, and recovery. It was created in 2004 with updates approximately every year. The last one took place in March 2019.
It is an open-source search service that provides such services as consulting, package matrix, embedding, enterprise support, etc. Indexing speed of Sphinx goes up to 10-15 MB/sec per core and HDD. First it was launched in 2001 with the last update in 2018.
This search engine library is created to help developers add search facilities and advanced indexing to their applications. It has partly evolved from Open Muscat engine which was first designed back in the 1980s. Updates take place every year or so with the latest version presented in September 2019.
The next step is to start the selected engine. Setting the analyzers and compound queries along with arranging the boosts for the fields are the main processes that you have to do at this step.
If you prefer using Elastic Search, as we do, you can use their own service. It makes the process of deployment, security, and operation of the Elastic Search on a large scale easy and fast.
When building a search engine software you have to determine the index structure. Even though it is a kind of database, it is important to remember that this is not the main data storage, neither it is a relational database. The index structure must be organized in a way that is convenient for the search. The data stored there also has to be the only one which is necessary for the search.
It is important to send the updated information from the database to the search engine. Some engines get this information directly from the database when in other cases you have to add a special code that completes this task. The search engine is more efficient when updates are rare. So, if there are dozens of queries per minute, it would be better to set the index update once per several minutes. This will allow sending numerous updates together.
Developers working with Elastic and using Python could utilize Github service and Celery to plan the index update.
At this stage, your search engine works well and might not require any additional work. Therefore, you can start making requests.
You can use different ranking algorithms that apply the data on the frequency of the word in texts and the engine knows that the main word in the “cardiology services” query, for example, is cardiology. You can use different ranking algorithms that apply the data about the word frequency in texts. So, in the phrase “cardiology services”, the engine can identify the word “cardiology” as the main one. Therefore, the results matching both words go first. Then, there will be the ones matching “cardiology” and the other ones matching “services”.
When working with Elastic, we prefer Elastic DSL. There are several reasons why:
This is where the first stage of creating the search engine design comes to an end and the second one begins.
This stage deals with other processes that help make your search engine more efficient.
First of all, you need to hire an expert who specializes in databases. Even though setting up a search is a technical task, a technical specialist may not be able to understand what kind of data users need and why. This is when a data specialist comes into use.
It’s important to find out if the results of your search engine are suitable for certain queries. It can be done by checking the user search history, choosing the top ten queries according to the popularity and letting an expert check their relevance.
Next, you have to formulate what documents are needed as a result. This is when you need to think about how you, as a human, would process such queries. For instance, you are working on scientific articles and as a result, you may get the following:
The final step is to find out why problems occur if there are such. Reading the information on how the engine search is built and the methods of its troubleshooting can be helpful. Sometimes you might need to readjust the basic principles to find the problem. However, sooner or later problems that require a debugging mode and detailed analysis will appear.
Depending on your search engine rules, you may need various ways to fix the query, which will always be interactive. So, identify the problems, sort them out and try to enjoy the process.
If you are working with Elastic, there are a few tips to help you make a search engine software for your business:
Use appropriate weights and boosts. There is a great book “Relevant Search With Applications for Solr and Elasticsearch” by Doug Turnbull and John Berryman that might be helpful.
To make your own search engine you need to hire specialists that meet your requirements. There are several alternatives. Let’s look at the pros and cons of each of them.
One of the options is to have an in-house team.
If you are not able to hire an in-house team, you may try to work with freelancers.
The third way, which many companies successfully use nowadays, is outsourcing the task to build a search engine software to an agency such as Gearheart, for example.
You can avoid such problems as mentioned above by choosing an agency wisely — it should have a good reputation and the skills of the developers have to meet your needs (this can be checked in their portfolios). And, of course, you should never hesitate to ask questions whenever they occur.
Creation of a search engine software is a great way to enhance the opportunities of your business. What’s more, it can be interesting and fun if you follow certain rules and enjoy the process. Engaging a professional team of developers working with a special agency like Gearheart is always an advantage for your project because the work is done by skilled developers. So, choose the approach that meets all your needs and set off for a developing journey.
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