As I see it an "order" should exist as a single document. The output of cat/indices returns a JSON array of Indices.In the article, High Traffic JSON Data into Elasticsearch on Kubernetes I demonstrate collecting weather data from the Dark Sky API.The weather data populates an Elasticssearch index based on the year and month. Instead you should be thinking in terms of documents or entities.
You are indexing data in a very SQL like way. We have created a web page which can help you evaluate a JSONPath. This topic is best understood by seeing it in action. Normally we'd just add the nifitimestamp attribute with the UpdateAttribute. It should look similar to this: Extracting data from MySQL. Referencing my previous posts, we've got NiFi pulling from MySQL and converting it directly to JSON. JSONPath defines expressions to traverse through a JSON document to reach to a subset of the JSON. At this point we've got Elasticsearch and Kibana ready for our logs. Intro to ELK: Get started with logs, metrics, data ingestion and custom vizualizations in Kibana. JSONPath creates a uniform standard and syntax to define different parts of a JSON document. Getting started with Elasticsearch: Store, search, and analyze with the free and open Elastic Stack. Using the 'q' parameter for search is equivalent to the 'query' option in JSON-formatted query string queries (which we'll get into. Next we need select the processor ExecuteSQLRecord. First we need to drag the processor onto the grid. For this tutorial you will need an AVRO schema called dttest and it’s contents are as follows.
#Json query elasticsearch nifi how to#
This is a shortcut way of accessing query string queries. In this tutorial I will guide you through how to add a processor for querying a SQL table to NiFi.
#Json query elasticsearch nifi series#
The second part of the series will build on this example to create a process group with two GetTwitter feeds: one with elasticsearch term filter and the other with a solr term filter. This question has many different answers and it really comes down to what you want to do with this data beyond what you are asking.Īssuming however that all you want to do is get all orders that contain a particular product, I'd advise changing your indexing structure a bit. The Elasticsearch-Hadoop (ES-Hadoop) connector lets you get quick insight from your big data and makes working in the Hadoop ecosystem even better. If you look at the Elasticsearch documentation for the Search APIs 'Search' page, you'll notice all the examples there use the 'q' parameter for search. This will allow us to query Elasticsearch using a fielded query like qtwitterFilterAttribute:elasticsearch.
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