Apache Solr Interview Questions and Answers
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Best Apache Solr Interview Questions and Answers
This blog is specially designed to provide you with frequently asked Apache Solr Interview Questions and Answers. If you want to enrich your career as a certified Solr Professional then you must get to know the frequently asked Apache Solr Interview Questions and Answers. To help you out, we have gathered a list of Solr Interview Questions and Answers. Mastering these questions would help you in cracking the Apache Solr Interview at a very first attempt and will land you in your dream job as an Apache Solr Professional. You can also learn all the essential Solr concepts by getting enrolled in CourseJet’s Apache Solr Training. Let’s get into the Solr Interview Questions.
Top Apache Solr Interview Questions and Answers
Apache Solr is the prominently used open-source enterprise search server built and developed on Apache Lucene. It is highly scalable, reliable, and fault-tolerant. Solr powers the navigation and search features of many largest internet sites. This Apache Solr platform is mainly used to build search applications. It is also known as the distributed database document with SQL support.
The acronym of SOLR is Short-Open-Load Reciprocal.
The significant difference between Apache Solr and Elasticsearch are as follows:
Apache Solr | Elasticsearch |
Apache Solr platform is mainly used to build search applications. It is an open-source enterprise search server built and developed on Apache Lucene | Elasticsearch is free and open-source. Elasticsearch is the best analytics and search engine for all types of data. |
Push Queries are not supported by Apache Solr | In Elasticsearch the push queries are supported by percolation |
Apache Solr is used for scalable search purpose | Elasticsearch is used for event-based information |
Supports Deduplication | Does not support Deduplication |
Indexing Speed is low in Apache Solr | Indexing Speed is faster and adjustable in Elasticsearch |
Deployment Complexity is medium in Apache Solr | In Elasticsearch also the deployment complexity is medium |
Apache Lucene is a most prominently used search engine library having search and indexing features. Lucene is designed and written in Java programming and is well supported by Apache Software Foundation. The python bindings are provided by PyLucene to the Apache Lucene core. Furthermore, Lucene has built-in capabilities like Tokenization, hit highlighting, and spell checking.
Apache Solr is the J2EE-based application that makes use of different Lucene libraries to provide user-friendly searches and indexes. The instance of Apache Solr runs as a multicore or single-core because it is a client-server model.
Faceting is the essential feature of Apache Solr. The main role of this feature is to classify the search results into different categories. This feature also determines the unique terms for a particular field and also returns the count for each specific term. The Facet function is very similar to the group-by clause in SQL.
SolrCloud is the most popular search engine having essential features like fault tolerance, high availability, etc. This cloud provides the best environment for distributing your content and queries across multiple servers. Apache Solr platform is mainly used to build search applications.
The essential features of Apache Solr are as follows:
- Easy Monitoring
- Real-time Indexing
- Fault Tolerance
- Highly Scalable
- High Availability
- Advanced Search Capabilities
- Flexible Query Parsing
- Full-Text Search Capabilities
- Supports standard-based open interfaces
- Adaptable and flexible faceting
Apache Solr Search platform is designed to support and scale larger implementations with minimum custom coding. Whereas, Autoscaling in Solr Search provides good defaults to make the SolrCloud cluster remain standalone and balanced in case of event changes in various clusters.
To install Apache Solr on your Windows, the system should have Java Runtime Environment (JRE) with the exact and correct version. The following steps are to be followed to install Solr.
- Step 1: Go to Command Prompt, then check the latest version of JRE in your System
- Step 2: If your system does not contain the latest version of JRE then you need to install it first.
- Step 3: Download the latest version of Apache Solr from the below Url. https://archive.apache.org/dist/lucene/solr/
- Step 4: Extract the zip folder from your machine and then go to extracted Solr folder
- Step 5: Get inside the example folder and then execute java -jar start.jar command.
- Step 6: Configure Solr with Drupal 7.x
- Step 7: Go to \apachesolr-7.x-1.8\apachesolr\solr-conf\solr-4.x and copy all the files to solr server directory [solr-4.6.1\example\solr\collection1\conf\] and replace them with existing files.
- Step 9: Solr Setup and Configuration is done. Finally, you need to index by visiting the default index page.
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Apache Solr platform is the most popular and Standalone enterprise search platform that is used to build search applications. It is an open-source search server built and developed on Apache Lucene. Solr includes a rich set of search parameters for controlling the highlighted terms. It works as the retrieval engine and the document storage for enhancing existing databases. This platform always ensures the best search results and it indexes the documents quickly if your files already exist in formats like CSV, JSON, XML, etc. In the next stage, the Solr processes the queries using the Query Request Handler. The main work of Apache Solr is to rank the results.
Solr Indexing is defined as the process of arranging the documents in a systematic manner. Apache Solr Index can accept data from various sources like CSV files, XML files, data from tables in the common file formats like PDF or Microsoft Word. Solr Indexing is the fast and easiest way to respond for search because it searches directly using indexes instead of texts directly.
The basic field types available in Apache Solr are as follows:
- BinaryField
- CurrencyField
- FloatField
- DateRangeField
- EnumField
- IntPointField
- TextField
- LongField
- PointTypeField
- TrieField
- StrField
- UUIDField
Apache Solr is the popularly used open-source enterprise search server built and developed on Apache Lucene. It is highly scalable, reliable, and fault-tolerant. Solr Search platform is the distributed document database with SQL support and executes the search in a distributed manner. Moreover, it is also a NoSQL Database with transactional support.
In Apache Solr, the document is the unit of index and search. In Solr, the data is organized into fields and documents. The documents consist of one or more fields in it. In another way, the Document is defined as the smallest unit of Solr.
The two different configuration files supported by Apache Solr are listed below.
- solrconfig.xml
- schema.xml
Apache Solr platform is the most prominent and Standalone enterprise search server that is used to build search applications. Solr powers the navigation and search features of many largest internet sites. Apache Solr Engine is the most widely used platform all over the world because it is easily deployable. It is designed and written in Java and it also provides both JSON API and RESTful XML Interface to make the building of search applications very easy.
The basic commands available in the Apache Solr platform are as follows:
- Start Command
- Stop Command
- Restart Command
- Help Command
- Status Command
An Apache Solr Core is considered as the key instance of the Lucene index that is used to single collection or index along with its associated configuration files and transaction logs. This Core consists of all the Solr Configuration files required to use.
The tokenizer is used to break the given text into sub-parts called tokens. The token is defined as the sequence of characters present in the text. The tokens derived from the text are passed through token filters to update, add, or remove tokens.
The syntax for Tokenizer is:
<fieldType name="text" class="solr.TextField">
<analyzer>
<tokenizer class="solr.StandardTokenizerFactory"/>
</analyzer>
</fieldType>
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Field Analyzer helps you a lot while working with textual data. It analyzes the field text and generates a token stream. An example of a Field Analyzer is given below.
<fieldType name="nametext" class="solr.TextField">
<analyzer class="org.apache.lucene.analysis.core.WhitespaceAnalyzer"/>
</fieldType>
In this case, WhitespaceAnalyzer is a single class which is responsible for the content analysis of the named text field and emitting the corresponding tokens.
Start command is used to start the Solr.
- To start Solr by using bin/solr start
- To start Solr in the background in your running Windows use bin/solr .cmd start syntax
To start Solr in the foreground simply use bin/solr start -f
When running Solr in Background use this bin/solr stop -p 8983 command to stop Solr. While running in the foreground you can stop Apache Solr using ctrl-c.
The schema.xml configuration file contains fields of documents and definitions of the field types.
The solrconfig.xml configuration file contains most of the parameters for configuring Solr and data directory. You can use this soleconfig.xml to create configuration overlays.
Apache Solr 8.6.1 is the latest version released on 13 August 2020.
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Best DevOps Interview Questions and Answers
The future is exactly yours when you are a DevOps engineer or willing to jump into the DevOps sector! 50% of the top the multinational companies around the globe is now implementing DevOps and they are in need of well-trained and certified DevOps engineers. Here you will find top 50 DevOps interview questions and answers asked by the top employers. Every fresher and professional DevOps engineers can make use of these DevOps interview questions to attend the interviews perfectly and sustain a perfect career in the future.
Most of the companies are now looking for DevOps professionals to carry out their business tasks. So entering into this field will be your cup of coffee. Never miss developing your DevOps skills. If you are already preparing for DevOps interview, then these top 50 DevOps interview questions and answers will be effective in evaluating your DevOps understanding and will be helpful in facing the interviews confidently. Just go through these DevOps interview questions and upgrade your skill. We wish you all success in your technical DevOps interview. Get placed in the top organizations and get paid more.
The IT nowadays is highly relying on DevOps which is actually collaboration or an effective communication between the software developers and the deployment or operational team. DevOps is used to deliver software quickly with low failure rates.
DevOps | Agile |
Ensures agility is both operations and development | Ensures holistic agility only in the development |
Both quality and timeliness are given equal priority | High priority is given only to the timeliness |
CI, CD, CT are some of the processes involved | Agile scrum, Agile kanban are some of the processes |
Self monitoring is the source of feedback | Customers are the source of feedback |
It is suitable for both agility and automation | Only agile |
A DevOps engineer requires Python scripting language which is simple and used to perform well in the DevOps sector.
An important component of agile process is continuous integration. Developers actually make changes to the features in no time and commit those changes to the version control repository. Once committed, developers can work on more effectively as the build can be checked on a regular basis but it is important for the developers to integrate the build with others so that they can receive feedback as early as possible.
An extension of continuous integration via which the developed features reach the end user within the specified time is known as continuous delivery. In this process, several quality analysis checkups and staging will be performed to check the accuracy of the feature before it reaches the production system.
As and when an application is effectively developed and deployed, it has to be monitored continuously so that we can unleash the error and make it right before it causes a major damage to the application.
The process of validating the developed and integrated code several times to ensure it works fine before it reaches the end-user is known as continuous testing.
To implement new highlights or features in no time and to debug errors instantly, developers can make use of DevOps. It is also helpful in furnishing clear communication between the colleagues.
There are several tools used in DevOps while some are listed below:
- Jenkins
- Ansible
- ELK (Elasticsearch, Logstash, Kibana)
- Jenkins
- Docker
- Nagios
- Monit
- Git
The two essential tools used for docker networking are Kubernetes and Docker Swarm.
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The commit that has introduced a bug with the help of binary search can be found easily with Git Bisect.
For effectively migrating the SVN to Git, we can use SubGit tool. With SubGit tool, we can also create or build a writable Git mirror for local or remote subversion repository.
Listed below are some of the key components of DevOps:
- Continuous Monitoring
- Continuous Integration
- Continuous Testing
- Continuous Delivery
A build is nothing but combining the source code together and checking whether the code works fine in the form of a single unit. While creating a build process, the source code will be put to various processes like compilation, inspecting, testing, and deployment.
The key aspects or the core principle of DevOps are listed below:
- Infrastructure as code
- Continuous deployment
- Automation
- Monitoring
- Security
A project management tool that is used to automate administration tasks are known as puppet.
The application development of DevOps undergo the below listed processes:
- Code building
- Code coverage
- Unit testing
- Packaging
- Deployment
The identification of two ways from the separate categories for the users is known as a two faction authentication which is known to ensure complete security.
Some of the cloud platforms that are used in DevOps implementation are as follows:
- Google Cloud
- Amazon Web Services
- Microsoft Azure
It is a pattern that minimizes the risk of bringing up new version software into the existing production environment. It can be achieved by introducing canary release to the subset of users before introducing it to the complete users available in a controlled manner.
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Below listed are some of the operations involved in the infrastructure of DevOps:
- Provisioning
- Configuration
- Orchestration
- Deployment
Continuous testing is the only method through which we can state that a new service is ready for production.
PTR which is known are the Pointer Record is maximum used in the reverse DNS lookup.
The powerful automation platform that transforms infrastructure into code effectively is known as a chef. Here we can use write scripts in order to automate any processes.
A resource is a piece of infrastructure in a specified desired state, which can be a package that has to be installed, a piece of service that has to run without interruptions or a file that has to be effectively generated.
The key functions of resource in chef are as follows:
- It can describe the desired state of any configuration
- It describes the steps to bring those configuration items to desired state
- It can specify some of the resource types like template, package and service
A collection of resources that describes everything that is used to configure any part of the system is known as a recipe.
Some of the core functions of recipe in chef are as follows:
- It is used to install and configure the software components
- It is used to manage files and deploy applications
- It can be used to execute other valid recipes too
A recipe is a collection of resources while a cookbook is a collection of recipes.
Some of the technical benefits of DevOps are as follows:
- Continuous and quick software delivery
- Lower complex issues that has to be fixed
- Quick solution to fix the problems
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Some of the business benefits of DevOps are as follows:
- Instant feature deliveries
- Operating environment is highly stable
- Rather than maintain and fix, you will have more time to add value
DevOps actually helps us to achieve faster production with lower failure rates. It also helps us to achieve easy, instant, and effective communication between the Ops and the Dev team to produce quality software without any hassles within the committed time frame.
A common usage followed mostly is the pattern while a pattern which is adopted by others that does not perform for any particular organization and we follow it without any doubts, then it is known as an anti-pattern.
Version control is a system that actually records the changes to a set of files or an individual file so far so that we can recall or go through the files later whenever needed. It comprises of a central shared repository through which the teammates can make changes to a set of file or an individual file.
Version control allows a user to do the following:
- To revert the files or an entire project back to their previous state
- To estimate the changes so far
- To find the last changes, and the person who made the change to avoid problems
- To find out who and when they introduced an issue
The benefits of version control system are as follows:
- With version control system, the teammates can work on any particular file at any time of their desire
- Version Control System (VCS) consist of all the past versions, files and variants
- As it holds all the project history and files, users can extract any data at any time even if the central server is crashed
- Also, we can get to know the complete changes made to the file exactly
Some of the prerequisites required to implement DevOps effectively are as follows:
- Need atleast a single version control system
- Need effective communication between colleagues
- Automated testing and deployment
The roles of configuration management in DevOps are as follows:
- It is used to manage and makes changes to several systems
- It is used to standardize resource configurations which will be used to manage IT infrastructure effectively
- It is used to manage and administer several servers and maintains efficient integrity of the holistic infrastructure
The roles of AWS in DevOps are as follows:
- AWS is used to automate complex tasks and it assures more time for the users to innovate new concepts in DevOps.
- With AWS service, users can manage single or thousands of instances effectively.
- Without the need to set up or install software, users can ensure a flexible and easy-to-use operation.
Continuous integration and continuous delivery are some of the services offered by CodePipleline. It ensures latest infrastructure updates, new software updates and features quickly. It makes it easier to perform building, testing and deploying as per defined by the user.
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A fully managed in-house build service that is used in the compilation of source code, testing, and introducing software packages that are ready to deploy are known as CodeBuild. This is automatically scaled and so ther is no need to manage, allocate to scale up the build servers. As the build operations are maintained concurrently, no builds will be left in the queue waiting.
The process of automating the deployment of code to any instance let it be a local server or Amazon’s EC2 instance is known as the CodeDeploy. It can actually simplify all the complexities that are associated in updating the application that is ready for release. The core advantange of CodeDeploy is that is fasten the activity of releasing several new builds and features thus neglecting the downtime which may occur during the process of deployment.
A single that performs several actions from developing, building operations to provisioning the methodologies of deployment for the AWS users is known as CodeStar. It is a single user interface that assists users in managing all the activities involved in software development. It is mainly used to set up a continuous pipeline of delivery that ensures rapid release of code into the production unit by the developers.
There are 3 important DevOps KPIs and they are:
- Meantime to failure recovery
- Deployment frequency
- Percentage of failed deployments
The only test that ensures complete recovery without any functionality or data loss after a major failure is known as the resilience test.
Pair programming is where a couple of programmers can work on the same system and on the same design, code or algorithm.
The meeting in which certain concepts like the failure and the steps to overcome those failures are discussed is known are post mortem meeting.
DevOps is used in the below listed sectors in wide:
- Production
- IT Operation
- Software Development
- Production Feedback
A lightweight virtualization that offers excellent isolation among processes is known as containers.
Dogpile effect is known as when a cache is expired and when the website is given several requests by the users at a single point of time. A semaphore lock is the only way which can prevent this effect.
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