4. Session Preparation
Download Elasticsearch 8.3.3
Download Kibana 8.3.3
run elasticsearch or elasticsearch.bat
Copy elastic user password
Copy Kibana token
run kibana or kibana.bat
Open Kibana URL and use Kibana token
Done
11. Lucene
Apache Lucene is an open source project available for free
Lucene is a Java library
Elasticsearch is built over Lucene and provides a JSON based REST API to refer to Lucene features
Elasticsearch provides a distributed system on top of Lucene
18. Shards
Each shard is in itself a fully-functional and independent "index" that can be hosted on any node in the cluster
index
shard 1 shard 2 shard 3
36. Big Data - Ingestion (cont.)
Ingest
Data Data
Logstash
37. Big Data - Query
Ingest
Data Data
Coordinating
38. Big Data - Multi Cluster
Node 1 Node 2 Node 3 Node 1 Node 2 Node 3
Cluster 1 Cluster 2
39. Big Data - Features
Rollup jobs Summarize and store historical data in a smaller index for future analysis
Transforms Use transforms to pivot existing Elasticsearch indices into summarized entity-centric
indices or to create an indexed view of the latest documents for fast access
ILM Makes it easier to manage indices in hot-warm-cold architectures, which are common
when you’re working with time series data such as logs and metrics
Data streams A data stream lets you store append-only time series data across multiple indices while
giving you a single named resource for requests
43. Aggregations
An aggregation summarizes your data as metrics, statistics, or other analytics
Metric Aggregations that calculate metrics, such as a sum or average, from field values
Bucket Aggregations that group documents into buckets, also called bins, based on field values, ranges,
or other criteria
Pipeline Aggregations that take input from other aggregations instead of documents or fields
44. Highlighting
Highlighters enable you to get highlighted snippets from one or more fields in your search results so you
can show users where the query matches are
45. Paginate search results
By default, searches return the top 10 matching hits
The from parameter defines the number of hits to skip, defaulting to 0
The size parameter is the maximum number of hits to return
Search after
46. Geospatial search
Elasticsearch supports two types of geo data: geo_point fields which support lat/lon pairs, and geo_shape
fields, which support points, lines, circles, polygons, multi-polygons, etc
48. Sort search results
Allows you to add one or more sorts on specific fields
The sort is defined on a per field level, with special field name for _score to sort by score, and _doc to
sort by index order
49. Elasticsearch SQL
Elasticsearch SQL aims to provide a powerful yet lightweight SQL interface to Elasticsearch
Elasticsearch SQL is built from the ground up for Elasticsearch
No need for additional hardware, processes, runtimes or libraries to query Elasticsearch
Elasticsearch’s SQL jdbc driver is a rich, fully featured JDBC driver for Elasticsearch
Elasticsearch SQL ODBC Driver is a 3.80 compliant ODBC driver for Elasticsearch
50. Scripting
With scripting, you can evaluate custom expressions in Elasticsearch
you can use a script to return a computed value as a field or evaluate a custom score for a query
painless
expression
mustache
51. Text analysis
Text analysis enables Elasticsearch to perform full-text search, where the search returns all relevant
results rather than just exact matches
Tokenization Breaking a text down into smaller chunks, called tokens. In most cases, these tokens
are individual words
This allows you to match tokens that are not exactly the same as the search terms, but
similar enough to still be relevant
Normalization
52. Pinned Query
Promotes selected documents to rank higher than those matching a given query
This feature is typically used to guide searchers to curated documents that are promoted over and above
any "organic" matches for a search
The promoted or "pinned" documents are identified using the document IDs stored in the _id field