ElasticSearch

Elastic Support Matrix at https://www.elastic.co/support/matrix. The installation instructions for all the supported platforms can be found in the Installing Elasticsearch documentation https://www.elastic.co/guide/en/elasticsearch/reference/7.0/install-elasticsearch.html

Elasticsearch configuration JVM heap size

# Xms represents the initial size of total heap space
# Xmx represents the maximum size of total heap space
-Xms1g
-Xmx1g

You rarely need to change the Java Virtual Machine (JVM) options unless the Elasticsearch server is moved to production. These settings can be used to improve performance. When configuring heap memory, please keep in mind that the Xmx setting is 32 GB at most, and no more than 50% of the available RAM.

Config Logging files

log4j2.properties: Elasticsearch uses Log4j 2 for logging. The log file location is made from three given properties, ${sys:es.logs.base_path}, ${sys:es.logs.cluster_name}, and ${sys:es.logs.node_name} in the log4j2.properties file, as shown in the code block:

appender.rolling.fileName = ${sys:es.logs.base_path}${sys:file.separator}${sys:es.logs.cluster_name}.log

For example, our installed directory is ~/elasticsearch-7.0.0. Since no base path is specified, the default value of ~/elasticsearch-7.0.0/logs is used. Since no cluster name is specified, the default value of elasticsearch is used. The log file location setting appender.rolling.filename will generate a log file named ~/elasticsearch-7.0.0/logs/elasticsearch.log

Comunicate with Elasticsearch usign API

curl -XGET 'http://localhost:9200'
{
 "name" : "wai",
 "cluster_name" : "elasticsearch",
 "cluster_uuid" : "7-fjLIFkQrednHgFh0Ufxw",
 "version" : {
 "number" : "7.0.0",
 "build_flavor" : "default",
 "build_type" : "tar",
 "build_hash" : "a30e8c2",
 "build_date" : "2018-12-17T12:33:32.311168Z",
 "build_snapshot" : false,
 "lucene_version" : "8.0.0",
 "minimum_wire_compatibility_version" : "6.6.0",
 "minimum_index_compatibility_version" : "6.0.0-beta1"
 },
 "tagline" : "You Know, for Search"
}

Python-Elasticsearch

Code to upload, download or process data in Elasticsearh

Descripción:

Servidor Jupyter instalado en AWS que permite interactuar con la data de ElasticCloud, permite cargar datos, descargar datos, procesar datos o hacer pruebas rápidas de algoritmos codificados en Python (por el momento) y la data de ElasticCloud.

Estructura de carpetas:

 |--bin: Contiene los ejecutables y programas.
 |
 |--nbconfig: Contiene archivos de configuración propios de Jupyter.
 |
 |--doc: Contiene archivos y documentos necesarios externos que se requieran cargar al servidor.
 |
 |--tmp: Contiene documentos temporales generados durante la ejecución de cualquier ejecutable o programa.
 |
 |--notebook: Contiene los Notebok para testear codigo Python.

WARNING: No modificar el archivo "jupyter_notebook_config.py".

Requirements

It's in /bin/requirements.txt

pip install -r requirements.txt

Types of DataBase No-SQL:

DB Key-Value:

Each element is identified by a unique key. Example: Cassandra, BigTable or HBase.

DB Documentaries:

This type stores the information as a document, as a simple json o xml structure, where it uses a unique key for each record. It also allows searches like key-value and more advanced aggregations. Examples: MongoDB, CouchDb or Elasticsearch.

DB Graph:

The ifnormation is represented as nodes of a graph and its realizations with the edges of graph, so that graph theory can be used to trraverse it. The information must be fully normalized. Examples: Neo4j, InfoGrid or Virtuoso.

DB Object Oriented

Information is represented by objects, similar to object-oriented programming languages. Examples: Zope, Gemstone or DB4o.

Documentation

https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html

hoat23 / ElasticSearch