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{ | |
"css/style.css": "css/style-13qet57adg9.css", | |
"img/logo-idealo.svg": "img/logo-idealo-kr3u2vv3k0r.svg", | |
"js/script.js": "js/script-09zyx87wvu6.js" | |
} |
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version: '3' | |
services: | |
master: | |
image: docker.elastic.co/elasticsearch/elasticsearch:6.5.4 | |
container_name: master | |
environment: | |
- cluster.name=elastic-cluster | |
- node.name=master | |
- node.master=true | |
- node.data=false |
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version: '3' | |
services: | |
esnode: | |
image: docker.elastic.co/elasticsearch/elasticsearch:6.5.4 | |
container_name: esnode | |
environment: | |
- node.name=esnode | |
- cluster.name=elastic-cluster | |
- discovery.type=single-node | |
- bootstrap.memory_lock=true |
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version: '3' | |
services: | |
esnode-earth: | |
image: docker.elastic.co/elasticsearch/elasticsearch:6.5.4 | |
container_name: esnode-earth | |
environment: | |
- cluster.name=elastic-cluster-earth | |
- node.name=esnode-earth | |
- bootstrap.memory_lock=true | |
- ES_JAVA_OPTS=-Xms512m -Xmx512m |
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version: '3' | |
services: | |
master: | |
image: docker.elastic.co/elasticsearch/elasticsearch:6.5.4 | |
container_name: master | |
environment: | |
- cluster.name=elastic-cluster | |
- node.name=master | |
- node.master=true | |
- node.data=false |
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version: '3' | |
services: | |
master: | |
image: docker.elastic.co/elasticsearch/elasticsearch:6.5.4 | |
container_name: master | |
environment: | |
- cluster.name=elastic-cluster | |
- node.name=master | |
- node.master=true | |
- node.data=false |
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version: '3' | |
services: | |
esv5node1: | |
image: docker.elastic.co/elasticsearch/elasticsearch:5.6.14 | |
container_name: esv5node1 | |
environment: | |
- cluster.name=elastic-cluster | |
- node.name=esv5node1 | |
- bootstrap.memory_lock=true | |
- xpack.security.enabled=false |
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# ** EXAM OBJECTIVES: INSTALLATION AND CONFIGURATION + CLUSTER ADMINISTRATION ** | |
# Our goal is to deploy an Elasticsearch cluster named `training-cluster`, which satisfies all the requirements that follows | |
# Add three nodes to `training-cluster`, and name them `node1`, `node2`, and `node3` | |
# Configure each node to be eligible as a master node | |
# Configure each node to be a data node, but not an ingest node | |
# Configure each node to disable swapping on its host | |
# Configure the JVM on each node to use a minimum and maximum of 8 GB for the heap | |
# Bind `node1` to the network address "192.168.0.100" | |
# Configure the Zen Discovery module of `node2` and `node3` to use the address (and default transport port) of `node1` | |
# Configure `training-cluster` so as to avoid the split brain scenario |
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# ** EXAM OBJECTIVES: INDEXING DATA + MAPPINGS AND TEXT ANALYSIS ** | |
# (remove, if present, any `hamlet*` index and index template) | |
# Create the index `hamlet_raw`, with one primary shard and four replicas | |
# Index in `hamlet_raw` a document that satisfies the following criteria: (i) has id "1"; (ii) has default type; (iii) has a field `line` with value "To be, or not to be: that is the question" | |
# Update the document with id "1" by adding the field `line_number` with value "3.1.64" | |
# Index in `hamlet_raw` a new document without specifying any id. The fields of this document are: (i) `text_entry` with value "Whether tis nobler in the mind to suffer"; (ii) `line_number` with value "3.1.66" | |
# Update the precedent document by setting `line_number` to "3.1.65" | |
# (in one request) Update all documents in `hamlet_raw` by adding a new field `speaker` with value "HAMLET" | |
# Update the document with id "1" by renaming the field `line` into `text_entry` | |
# Delete the `hamlet_raw` index |
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# ** EXAM OBJECTIVES: MAPPINGS AND TEXT ANALYSIS ** | |
# (remove, if present, any `hamlet*` index and index template) | |
# Create the index `hamlet_1`, with one primary shard and no replicas | |
# Define the mapping for `hamlet_1`, satisfying the following criteria: (i) has a type "_doc" with three string fields named `speaker`, `line_number`, and `text_entry`; (ii) only `text_entry` is analysed; (iii) `text_entry` has a multi-field named `english`, associated with the built-in "english" analyzer; (iv) no aggregations supported by `line_number` | |
# Populate `hamlet_1` by running the _bulk command with the request-body below | |
{"index":{"_index":"hamlet_1","_id":0}} | |
{"line_number":"1.1.1","speaker":"BERNARDO","text_entry":"Whos there?"} | |
{"index":{"_index":"hamlet_1","_id":1}} | |
{"line_number":"1.1.2","speaker":"FRANCISCO","text_entry":"Nay, answer me: stand, and unfold yourself."} | |
{"index":{"_index":"hamlet_1","_id":2}} |
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