Elasticsearch
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How to Use the Synonyms Feature Correctly in Elasticsearch
Synonyms are used to improve search quality and broaden the scope of what is considered a matching. For example, a user searching for “England” might expect to find documents that contain “British” or “UK” as well, although these three words are totally different. The synonyms feature in Elasticsearch is very powerful and can make your… Continue reading
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Write Elasticsearch Queries with Logical Conditions using query_string in a Simpler Way
When it goes to boolean operations such as NOT, AND, and OR, we normally use bool queries with must, should, must_not clauses. Yes, bool queries are very powerful and can be used to perform all types of advanced searches. However, for simple searches with basic NOT, AND, and OR conditions, using bool queries would be… Continue reading
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How to Index Elasticsearch Documents with the Bulk API in Python
When we need to create an Elasticsearch index, the data sources are normally not normalized and cannot be imported directly. The original data can be stored in a database, in raw CSV/XML files, or even obtained from a third-party API. In this case, we need to pre-process the data to make it work with the… Continue reading
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Important Syntax Updates of Elasticsearch 8 in Python
There are quite a few breaking changes in version 8 of the Elasticsearch Python client library, which will give you a lot of trouble when you update the library from version 7 to 8. Even though it can be a painful task, it is still recommended to update the library to the latest version because… Continue reading
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How to Run Elasticsearch 8 on Docker for Local Development
For the new major version of Elasticsearch (8.x.x), there are significant updates on running Elasticsearch and Kibana on Docker. The commands and syntax for Docker and Docker Compose that used to work for previous versions would need to be updated in order to work for the latest version. In this post, we will introduce how… Continue reading
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Learn advanced CRUD and search queries for nested objects in Elasticsearch from practical examples
In this article, some advanced CRUD and search queries for nested objects in Elasticsearch will be introduced. We will focus on nested objects, which are advanced topics in Elasticsearch. You can run this command in Kibana to create the index which will be used later. In this example, the attributes field is a nested field… Continue reading
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Learn Elasticsearch queries from practical examples
Elasticsearch is the most popular open-source enterprise search engine widely used in the industry. We have learned what it is and why it is so fast. We have also learned how to use Elasticsearch in Python. An index laptops-demo have been created and filled with some sample data on which the queries in this article… Continue reading
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All you need to know about using Elasticsearch in Python.
In this article, we are going to talk about how to use Elasticsearch in Python. As a data engineer, you may need to create Elasticsearch documents in Python with some scripts. As a software engineer, when you design your API in Python, you would need to make REST API calls to Elasticsearch to fetch the… Continue reading
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What is Elasticsearch and why is it so fast
Elasticsearch is the most popular open-source enterprise search engine based on the Lucene library, which allows the creation of indices on every field of a document by default. Another popular search engine based on the Lucene library is Apache Solr. Solr is a mature and also widely used search engine. We can’t easily say which… Continue reading