Home » Author Archives: Florian Hopf

Author Archives: Florian Hopf

Florian is working as a freelance software developer and consultant in Karlsruhe, Germany. The main focus of his work is information retrieval with Lucene, Solr and Elasticsearch. He is one of the organizers of the Java User Group in Karlsruhe.

Fixing Elasticsearch Allocation Issues

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Last week I was working with some Logstash data on my laptop. There are around 350 indices that contain the logstash data and an index that holds the metadata for Kibana 4. When trying to start the single node cluster I have to wait a while, until all indices are available. Some APIs can be used to see the progress ...

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Logging to Redis using Spring Boot and Logback

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When doing centralized logging, e.g. using Elasticsearch, Logstash and Kibana or Graylog2 you have several options available for your Java application. You can either write your standard application logs and parse those using Logstash, either consumed directly or shipped to another machine using something like logstash-forwarder. Alternatively you can write in a more appropriate format like JSON directly so the ...

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Use Cases for Elasticsearch: Analytics

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In the last post in this series we have seen how we can use Logstash, Elasticsearch and Kibana for doing logfile analytics. This week we will look at the general capabilities for doing analytics on any data using Elasticsearch and Kibana. Use Case We have already seen that Elasticsearch can be used to store large amounts of data. Instead of ...

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Use Cases for Elasticsearch: Index and Search Log Files

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In the last posts we have seen some of the properties of using Elasticsearch as a document store, for searching text content and geospatial search. In this post we will look at how it can be used to index and store log files, a very useful application that can help developers and operations in maintaining applications. Logging When maintaining larger ...

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Use Cases for Elasticsearch: Geospatial Search

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In the previous posts we have seen that Elasticsearch can be used to store documents in JSON format and distribute the data across multiple nodes as shards and replicas. Lucene, the underlying library, provides the implementation of the inverted index that can be used to search the documents. Analyzing is a crucial step for building a good search application.   ...

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Use Cases for Elasticsearch: Flexible Query Cache

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In the previous two posts on use cases for Elasticsearch we have seen that Elasticsearch can be used to store even large amounts of documents and that we can access those using the full text features of Lucene via the Query DSL. In this shorter post we will put both of use cases together to see how read heavy applications ...

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Use Cases for Elasticsearch: Full Text Search

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In the last post of this series on use cases for Elasticsearch we looked at the features Elasticsearch provides for storing even large amounts of documents. In this post we will look at another one of its core features: Search. I am building on some of the information in the previous post so if you haven’t read it you should ...

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Use Cases for Elasticsearch: Document Store

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I’ll be giving an introductory talk about Elasticsearch twice in July, first at Developer Week Nürnberg, then at Java Forum Stuttgart. I am showing some of the features of Elasticsearch by looking at certain use cases. To prepare for the talks I will try to describe each of the use cases in a blog post as well. When it comes ...

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Goodbye Sense – Welcome Alternatives?

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I only recently noticed that Sense, the Chrome Plugin for Elasticsearch has been pulled from the app store by its creator. There are quite strong opinions in this thread and I would like to have Sense as a Chrome plugin as well. But I am also totally fine with Elasticsearch as a company trying to monetize some of its products ...

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An Alternative to the Twitter River – Index Tweets in Elasticsearch with Logstash

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For some time now I’ve been using the Elasticsearch Twitter river for streaming conference tweets to Elasticsearch. The river runs on an Elasticsearch node, tracks the Twitter streaming API for keywords and directly indexes the documents in Elasticsearch. As the rivers are about to be deprecated it is time to move on to the recommended replacement: Logstash. With Logstash the ...

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