Querying Elasticsearch

Swatee Chand has a tutorial on querying Elasticsearch:

In Elasticsearch, aggregations framework is responsible for providing the aggregated data based on a search query. Aggregations can be composed together in order to build complex summaries of the data. For a better understanding, consider it as a unit-of-work. It develops analytic information over a set of documents that are available in Elasticsearch. Various types of aggregations are available, each of them having its own purpose and output. For simplification, they are generalized to 4 major families:

  1. Bucketing

    Here each bucket is associated with a key and a document. Whenever the aggregation is executed, all the buckets criteria are evaluated on every document. Each time a criterion matches, the document is considered to “fall in” the relevant bucket.

  2. Metric

    Metrics are the aggregations which are responsible for keeping a track and computing the metrics over a set of documents.

  3. Matrix

    Matrix are the aggregations which are responsible for operating on multiple fields. They produce a matrix result out of the values extracted from the requested document fields. Matrix does not support scripting.

  4. Pipeline

    Pipeline are the aggregations which are responsible for aggregating the output of other aggregations and their associated metrics together.

If you deal with Elasticsearch (or have log data that you want to query through), this tutorial will give you an idea of what you can do.

Related Posts

Amazon Elasticsearch Alerts

Jon Handler shows how to create alerts for Amazon Elasticsearch Service: On April 8, Amazon ES launched support for event monitoring and alerting. To use this feature, you work with monitors—scheduled jobs—that have triggers, which are specific conditions that you set, telling the monitor when it should send an alert. An alert is a notification that the triggering condition occurred. […]

Read More

Kafka In Front of ELK

Daniel Berman sets up a simple Elasticsearch-Logstash-Kibana (ELK) stack and throws Kafka in front of it: To perform the steps below, I set up a single Ubuntu 16.04 machine on AWS EC2 using local storage. In real-life scenarios you will probably have all these components running on separate machines. I started the instance in the […]

Read More

Categories

November 2017
MTWTFSS
« Oct Dec »
 12345
6789101112
13141516171819
20212223242526
27282930