Nodes become automatically parts of a cluster and, during setup, node tries to join the cluster
Default settings and values are such that default configuration is enough to immediately use ElasticSearch. Replicas provide to relieve the load on a single node that cannot handle all requests and provide greater data security because, if you lose data from the original shard, you can recover them on the replica.ĮlasticSearch collects a lot of info about cluster state, index settings, and stores them into the gateway.Īrchitecturally, ElasticSearch, is based on some simple key concepts: Replica is a copy of shard that you can use to query in same mode of original shard. ElasticSearch automatically manages sharding so final user seems to be just a one big index. These indexes are called Shard, and spreading process is called sharding. To let cluster a right functioning, ElasticSearch spreads data over several physical indexes of Apache Lucene. You can configure a cluster so that, even if some nodes are not available, search and management feature are guaranteed. In that case, you can use a multi-node Cluster, a set of nodes working together to manage a heavier load than a single instance is not able to handle. A single node can be enough for a lot of cases of use, but sometimes you need to manage faults or maybe you have too data to manage with a single node. That allows to store various document types on the same index and get several mappings for several types.Ī single instance of ElasticSearch server is called Node. This analysis process – called mapping – is performed by filtering data content (for instance, removing HTML tags) and tokenize it, so that documents are splitted in tokens.Įach document in ElasticSearch has a type. It’s just a JSON object.Īll documents are analyzed before being stored. Each documents may have a set of fields and no schema or defined structure is given. It consists of a set of fields with names and one or more values. The index of ES is quite similar to the SQL DB one, because we use it to store and read documents.ĭocument is the main entity of ElasticSearch world. Let’s try to understand what the basic concepts are.ĮlasticSearch stores data in one or more indexes. Specifically, we are talking about an open source full-text search engine based on Apache Lucene, with which manages the indexing of documents and research. Then, We searched the market for third-party products that could fit our needs and, after an in-depth analysis, we have chosen to adopt ElasticSearch: a distributed, easily adaptable search engine that manages research and analysis, working on the REST protocol too, facilitating the extrapolation and transformation of data. To optimize the time, we tried to add a cache layer between service and DB level in order to avoid stressing too much the DB, but we were not satisfied about the results. We tried the implementation of custom searches, based on the search of a given string on all the fields of an object. I’d bet you’ve certainly been asked to add advanced search features to your Web application, and often a full-text Google-like search.ĭuring the development of an e-commerce of technology, we were asked to allow users to perform advanced research on the products, so that they could find, efficiently and completely, what they were looking for.
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