glenacota

# GOAL: Secure a cluster and an index using Elasticsearch Security
# INITIAL SETUP: (i) a running Elasticsearch cluster with at least one node and a Kibana instance, (ii) no index named `hamlet`
# Copy-paste the following instructions into your Kibana console, and work directly from there

# Enable xPack security on the cluster
# Set the password of the `elastic` and `kibana` built-in users, by using the pattern "{{username}}-password" (e.g., "elastic-password")
# Login to Kibana using the `elastic` user credentials
# Create the index `hamlet` and add some documents by running the following _bulk command
PUT hamlet/_doc/_bulk
{"index":{"_index":"hamlet","_id":0}}

glenacota

# GOAL: Deploy an Elasticsearch cluster that satisfies a given set of requirements
# INITIAL SETUP: /

# Download the latest 6.x version of Elasticsearch and Kibana
# Deploy the cluster `eoc-01-cluster`, so that it satisfies the following requirements: (i) has three nodes, named `node1`, `node2`, and `node3`, (ii) all nodes are eligible master nodes
# Configure the nodes to avoid the split brain scenario
# Configure `node1` so that the node (i) is a data node but not an ingest node, (ii) is bound to the network address "192.168.0.100" and HTTP port "9201", (iii) doesn't allow swapping on its host
# Configure the Zen Discovery module of `node2` and `node3` to use the address and default transport port of `node1`
# Configure the JVM settings of each node so that it uses a minimum and maximum of 8 GB for the heap
# Configure the logging settings of each node so that (i) the logs directory is not the default one, (ii) the log level for transport-related events is set to "debug"

glenacota

# GOAL: Allocate the shards in a way that satisfies a given set of requirements
# INITIAL SETUP: /

# Download the latest 6.x version of Elasticsearch and Kibana
# Deploy the cluster `eoc-06-cluster`, with three nodes named `node1`, `node2`, and `node3`
# Configure the Zen Discovery module of each node so that they can communicate with each other
# Connect a Kibana instance to `node3`
# Start the cluster
# Create the index `hamlet-1` with two primary shards and one replica
# Add some documents to `hamlet-1` by running the following _bulk command

glenacota

# GOAL: Backup and cross-cluster search
# INITIAL SETUP: /

# Download the latest 6.x version of Elasticsearch and Kibana
# Deploy the cluster `eoc-06-earth-cluster`, with one node named `node-earth`
# Connect a Kibana instance to `node-earth`
# Start the cluster
# Create the index `hamlet` and add some documents by running the following _bulk command
PUT hamlet/_doc/_bulk
{"index":{"_index":"hamlet","_id":0}}

glenacota

# GOAL: Create, update and delete indices while satisfying a given set of requirements
# INITIAL SETUP: (i) a running Elasticsearch cluster with at least one node and a Kibana instance, (ii) no index or index template that starts by `hamlet`
# Copy-paste the following instructions into your Kibana console, and work directly from there

# Create the index `hamlet-raw` with one primary shard and four replicas
# Add a document to `hamlet-raw`, so that the document (i) has id "1", (ii) has default type, (iii) has a field named `line` with value "To be, or not to be: that is the question"
# Update the document with id "1" by adding a field named `line_number` with value "3.1.64"
# Add a new document to `hamlet-raw`, so that the document (i) has no explicit id, (ii) has default type, (iii) has a field named `text_entry` with value "Whether tis nobler in the mind to suffer", (iv) has a field named `line_number` with value "3.1.66"
# Update the last document by setting the value of `line_number` to "3.1.65"
# In one 

glenacota

# GOAL: Create index templates that satisfy a given set of requirements
# INITIAL SETUP: (i) a running Elasticsearch cluster with at least one node and a Kibana instance, (ii) no index or index template that starts by `hamlet`
# Copy-paste the following instructions into your Kibana console, and work directly from there

# Create the index template `hamlet_template`, so that the template (i) matches any index that starts by "hamlet_" or "hamlet-", (ii) allocates one primary shard and no replicas for each matching index
# Create the indices `hamlet2` and `hamlet_test`
# Verify that only `hamlet_test` applies the settings defined in `hamlet_template`
# In one request, delete both `hamlet2` and `hamlet_test`
# Update `hamlet_template` by defining a mapping for the type "_doc", so that (i) the type has three fields, named `speaker`, `line_number`, and `text_entry`, (ii) `speaker` and `line_number` map to a unanalysed string, (iii) `text_entry` uses an "english" analyzer
# Create the index `hamlet-1` and add some 

glenacota

# GOAL: Create an alias, reindex indices, and create ingest pipelines
# INITIAL SETUP: (i) a running Elasticsearch cluster with at least one node and a Kibana instance, (ii) no index or index template that starts by `hamlet`
# Copy-paste the following instructions into your Kibana console, and work directly from there

# Create the indices `hamlet-1` and `hamlet-2`, each with two primary shards and no replicas
# Add some documents to `hamlet-1` by running the following _bulk command
PUT hamlet-1/_doc/_bulk
{"index":{"_index":"hamlet-1","_id":0}}
{"line_number":"1.1.1","speaker":"BERNARDO","text_entry":"Whos there?"}
{"index":{"_index":"hamlet-1","_id":1}}

glenacota

# ** EXAM OBJECTIVE: INSTALLATION AND CONFIGURATION **
# GOAL: Setup an Elasticsearch cluster that satisfies a given set of requirements
# REQUIRED SETUP: /

glenacota

POST _opendistro/_sql?format=csv&separator=%3B
{
  "query": "SELECT * FROM *"
}

glenacota

# Based on the query pusblished in the question, I added the following documents to the index.

[
  {
    "@timestamp" : "2020-01-15",
    "condition" : "B",
    "value" : 10,
    "conditionType" : "ABCD"
  },
  {