Introduction to Apache SolrCloud
Apache SolrCloud is an extension of Solr 4.0 encompassing new features and functionalities. This extension of Solr is highly scalable, fault-tolerant and distributed in nature that allows the users to perform real-time searching, configuring the centralized cluster, etc. Unlike the old master-slave cluster, SolrCloud automates many of the processes with the help of Zookeeper. Precisely SolrCloud aims to provide a seamless flow of operations by automating the tasks that were performed manually in master-slave cluster.
Terminologies Used in SolrCloud Architecture
In order to understand the architecture of SolrCloud, one should be familiar with the following terminologies:
| Terminology | Description |
| Cluster | A collection of Solr nodes managed as a single unit. |
| Node | JVM instance which runs Solr. |
| Partition | The set of entire documents. |
| Shard | The collection of more than one nodes where a partition is stored. |
| Leader | Directs the documents belonging to the partition. |
| Collection | Combination of one or more than one shards. |
| Replication Factor | Minimum times a document is copied and maintained by the cluster. |
| Transaction Log | A record of the write operations maintained by every node. |
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Why should we use Apache SolrCloud?
After learning about the architecture, you must have gotten a fair idea about what comprises of SolrCloud cluster. However it is also important to know why you should use SolrCloud despite having other applications providing similar functionality. Read below to know:
- Unlike the classic versions of Solr, the configuration files are stored in ZooKeeper instead of file system.
- SolrCloud’s unique architecture allows it to eliminate the limitations of master-slave cluster by automating the process of update and search.
- Various new fields and commands are introduced such as ‘Update log’ and ‘-version-’ to help in the process of recovery, coordination, election, etc.
- Apache SolrCloud allows the users to search the distributed files across collections as long as the compatibility remains.
- The moment a query is sent to a node, Solr performs a full distributed search across the cluster.
- Any update sent to any node is automatically forwarded to the respective Shard and gets replicated. These updates are generally sent to the leader.
- The interface is improved facilitating better management and error reporting.
- New field is introduced to update a document in near real-time.
- A new feature of Spellchecker is introduced allowing the users to refer to the main index for the cluster to suggest the spellings.
Architecture of Apache SolrCloud: A brief comparison with master-slave cluster
There are some minor differences between these two architectures which result in drastic changes in the outcomes. Let us see what those changes are:
Unlike master-salve cluster, SolrCloud architecture requires additional ZooKeeper Nodes. This clearly indicates that the normal size of a SolrCloud cluster is much bigger than master-slave. However an important point to be noted here is that these nodes of ZooKeeper are not required to be specifically powerful as their roles are limited to monitoring and maintaining the status of the nodes. Since latency plays more important role than the computing power, hence the ZooKeeper nodes remain as the minimal machines as long as they are serving the purpose. Collection API’s and CoreAdmin API’s are introduced in this version, which is a big improvement over the older versions.
Scope of Apache SolrCloud
With massive amounts of big data generating everyday minute, it is utmost important for the companies to index and classify the data in such a way that make it highly searchable by the users. Many of the technologies fail after certain extent and provide cluttered and ambiguous responses. However Apache SolrCloud addresses this issue by implementing appropriate indexing logic which helps the users to access the data easily.
Though SolrCloud still requires refinement in its existing functionality but it is getting better with every new release. It is evident that the graph of SolrCloud is going up with these gradual improvements and better features. SolrCloud has already automated many of the features which were previously performed manually. There are many more features which are supposed to be inculcated in coming years.
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When is Apache SolrCloud suitable for you?
Apache SolrCloud provides various benefits over other similar technologies. But how to decide in which cases it would be beneficial to use SolrCloud? Read below:
- When you want continuous processing
- If you need the fail-over feature
- When you want automated activities
First, SolrCloud allows the users to continue working on the technology for a long time without any interruption till at least one server is present and is hosting every shard. Moreover it is also possible to get the documents back even if all the servers are down. Second, if you are working on a big cluster, the servers or nodes may fail sometimes. However while using SolrCloud the user would not have to worry as even if the leader node is killed accidentally, the new leader is automatically chosen by the system and the entire process resumes.
Third, many of the processes were manually done by the users such as talking to the shards, adding documents to the shards, etc. SolrCloud automated these activities by introducing latest features into the older version.
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Who is the right audience to learn Apache SolrCloud?
The big data world is an open platform offering diverse job opportunities to people belonging to different areas of expertise. However, for the candidates wanting to see themselves as Solr Developers, Project Managers, Mainframe Professionals, System Administrators, Search Analysts, etc., learning Apache SolrCloud will give you guaranteed success.
However, having a basic knowledge of Big Data Hadoop and Apache HBase is recommended for beginners.
How will Apache SolrCloud help in your career growth?
A report by indeed.com reveals that the Implementation experts of Apache Solr earn around $105,000 in a month.
Moreover, the job portals are overwhelmed by the availability of postings demanding Solr professionals. With the big data market growing bigger every day, the opportunities for beginners and experience holders are only going to grow in the future allowing the candidates to find better Apache SolrCloud jobs as per their expertise.
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