Error using Notebook "Streaming structured data from Elasticsearch using Tensorflow-IO" when it is tested in local environment - tensorflow

Question

I got the notebook "Streaming structured data from Elasticsearch using Tensorflow-IO" in my PC.
"This tutorial focuses on streaming data from an Elasticsearch cluster into a tf.data.Dataset which is then used in conjunction with tf.keras for training and inference."
Follow instructions, elasticsearch has been locally installed (Windows 10, ELK version 1.9)
The step by step run Ok but in step "Training dataset", when the exercise goes to read DataSets from "Train" and "Test" indexes, the notebook display the error "Skipping node:
http://localhost:9200/_cluster/health" with additional info:
"ConnectionError: No healthy node available for the index: train, please check the cluster config"
I check indexes status (http://localhost:9200/_cat/indices?v=true&s=index) and the response from elasticsearch is according to expectations:
health status index uuid pri rep docs.count docs.deleted store.size pri.store.size
yellow open test EKQKEYWCSBOLY1-8-dqeUg 1 1 3462 0 306.7kb 306.7kb
yellow open train 8D4LF-TqRQ6f-CZmgnhM9g 1 1 8075 0 698.9kb 698.9kb
Runnign the same notebook in Colab environment, the execises goes OK, without errors.
My environment:
OS: Windows 10
tensorflow-io version: 0.17.0
tensorflow version: 2.4.1
curl -sX GET "localhost:9200/"
{
"name" : "nnnnnnnnnnn",
"cluster_name" : "elasticsearch",
"cluster_uuid" : "_fdrIUXPScCIPqOCvPPorA",
"version" : {
"number" : "7.9.0",
"build_flavor" : "default",
"build_type" : "zip",
"build_hash" : "a479a2a7fce0389512d6a9361301708b92dff667",
"build_date" : "2020-08-11T21:36:48.204330Z",
"build_snapshot" : false,
"lucene_version" : "8.6.0",
"minimum_wire_compatibility_version" : "6.8.0",
"minimum_index_compatibility_version" : "6.0.0-beta1"
},
"tagline" : "You Know, for Search"
}
Python 3.8.5 (default, Sep 3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]

Answer 1

This is a couple of months too late but the reason this happens is likely due to missing core ops dependency (which the ElasticsearchIODataset function relies on) in the windows distribution of tensorflow-io. Maybe try this from a linux wsl environment instead..