To know more about What is aggregations in Elasticsearch?
- Metrics aggregations
- Avg aggregation
- Cardinality aggregation
- Extended stats aggregation
- Min & Max aggregation
- Sum aggregation
- Bucket aggregations
- Nested Bucket aggregations
Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data so you can discover the expected and uncover the unexpected.
For the course Web Search, together with a teammate I made a tool to analyse online political election news, using web crawling techniques. Specifically, we were interested in whether online political news coverage was correlated with election results.
Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data so you can discover the expected and uncover the unexpected.
For the course Web Search, together with a teammate I made a tool to analyse online political election news, using web crawling techniques. Specifically, we were interested in whether online political news coverage was correlated with election results.
Presentation about http://worldwidesemanticweb.org/ given at SugarCamp#3 in Paris on April 12-13. The slides introduce the activities of the WWSW group centred around adapting Semantic Web technologies to be usable in challenging conditions.
The XML Business Reporting Language (XBRL) is a standard for business and financial information reporting. It is based on XML so instance documents based on XBRL, e.g. a quarterly report, are highly constrained by the XML document-oriented nature. This makes more difficult to perform queries that mix information from filings from different dates, companies, or accounting principles than with a formalism based on a graph model instead of a tree model. Semantic Web technologies provide a graph model that facilitates mashing-up different XBRL sources. We have put into practice this approach mapping the XBRL filings available from the SEC’s EDGAR program to Resource Description Framework (RDF) and the XML Schema taxonomies these filings are based on to Web Ontology Language (OWL). The resulting semantic metadata, though highly tied to the XML structure it is mapped from, benefits from Semantic Web technologies and tools in order to facilitate integration and cross-querying, even together with other parts of the Web of Linked Data.
FinTech and InsuranceTech case studies digitally transforming Europe's future with BigData and AI
The new data-driven industrial revolution highlights the need for big data technologies to unlock the potential in various application domains. The insurance and finance services industry is rapidly transformed by data-intensive operations and applications. FinTech and InsuranceTech combine very large datasets from legacy banking systems with other data sources such as financial markets data, regulatory datasets, real-time retail transactions, and more, improving financial services and activities for customers.
An introduction to and a couple of examples and tips on how to use Elasticsearch for general data analytics. Examples are based on Elasticsearch version 2.x.
Aggregations - The Elasticsearch "GROUP BY"John Sobanski
Presented at Elastic's worldwide "Virtual Meetup" on 5/15/2024
https://www.youtube.com/watch?v=ayQap5pH_0w
https://john.soban.ski/aggregations-the-elasticsearch-group-by.html
Logging and ranting / Vytis Valentinavičius (Lamoda)Ontico
HighLoad++ 2017
Зал «Пекин+Шанхай», 7 ноября, 16:00
Тезисы:
http://www.highload.ru/2017/abstracts/2842.html
A story about real life experience in Lamoda, featuring logging, forest animals, limited size buffers and morning routines.
Possible takeaways from this presentation:
1. Understanding the need of central log aggregation
2. Learning a few tips about logging and event aggregation
3. Saving a lot of money by implementing your own personal "poor-man's" NewRelic
...
Precog & MongoDB User Group: Skyrocket Your Analytics MongoDB
earn how to do advanced analytics with the Precog data science platform on your MongoDB database. It's free to download the Precog file and after installing, you'll be on your way to analyzing all the data in your MongoDB database, without forcing you to export data into another tool or write any custom code. Learn more here: www.precog.com/mongodb
Presentation held during SFScon15 - Free Software Conference, 13.11.2015 @ TIS innovation park, Bolzano
--
Most developers use databases to support their projects. However, database systems are normally seen as a “black box” to which a developer passes a query in order to get data.
This talk gives some insights in how a query is processed inside PostgreSQL. It provides a step-by-step walk through the different stages of the database backend. It starts with the analysis of the query syntax, explains the planning of the query execution, and finally shows how the result is retrieved.
If you got hungry for more, have a look at the more detailed workshop that follows.
This talk moves beyond the standard introduction into Elasticsearch and focuses on how Elasticsearch tries to fulfill its near-realtime contract. Specifically, I’ll show how Elasticsearch manages to be incredibly fast while handling huge amounts of data. After a quick introduction, we will walk through several search features and how the user can get the most out of the Elasticsearch. This talk will go under the hood exploring features like search, aggregations, highlighting, (non-)use of probabilistic data structures and more.
OSMC 2014: Introduction into collectd | Florian FosterNETWAYS
Periodically measuring performance metrics of production systems allows administrators and developers to analyze system behavior during and after outages, quantify performance improvements, and detect trends and take proactive measures before problems arise. Performance metrics are also interesting for alerting, because they can be aggregated meaningfully, thereby basing an alert on a group of hosts rather than each host individually, for example.
This talk will give an introduction to collectd, an open-source tool to gather, process and store performance metrics. A sample setup which aggregates a couple of metrics and stores the aggregate in Graphite will be presented. Afterwards, we will show how the collectd-nagios utility can be used to define alerts in Icinga based on this data.
PCU@RISE 2017 - Building a thesaurus for product searchPCU Consortium
In the field of ecommerce, search is very important, but very specific. Smile provides in Magento Elastic Suite a thesaurus that addresses these specificities, and aims at enhancing it with Machine Learning in its new PCU R&D projects along with its partners.
Presentation about http://worldwidesemanticweb.org/ given at SugarCamp#3 in Paris on April 12-13. The slides introduce the activities of the WWSW group centred around adapting Semantic Web technologies to be usable in challenging conditions.
The XML Business Reporting Language (XBRL) is a standard for business and financial information reporting. It is based on XML so instance documents based on XBRL, e.g. a quarterly report, are highly constrained by the XML document-oriented nature. This makes more difficult to perform queries that mix information from filings from different dates, companies, or accounting principles than with a formalism based on a graph model instead of a tree model. Semantic Web technologies provide a graph model that facilitates mashing-up different XBRL sources. We have put into practice this approach mapping the XBRL filings available from the SEC’s EDGAR program to Resource Description Framework (RDF) and the XML Schema taxonomies these filings are based on to Web Ontology Language (OWL). The resulting semantic metadata, though highly tied to the XML structure it is mapped from, benefits from Semantic Web technologies and tools in order to facilitate integration and cross-querying, even together with other parts of the Web of Linked Data.
FinTech and InsuranceTech case studies digitally transforming Europe's future with BigData and AI
The new data-driven industrial revolution highlights the need for big data technologies to unlock the potential in various application domains. The insurance and finance services industry is rapidly transformed by data-intensive operations and applications. FinTech and InsuranceTech combine very large datasets from legacy banking systems with other data sources such as financial markets data, regulatory datasets, real-time retail transactions, and more, improving financial services and activities for customers.
An introduction to and a couple of examples and tips on how to use Elasticsearch for general data analytics. Examples are based on Elasticsearch version 2.x.
Aggregations - The Elasticsearch "GROUP BY"John Sobanski
Presented at Elastic's worldwide "Virtual Meetup" on 5/15/2024
https://www.youtube.com/watch?v=ayQap5pH_0w
https://john.soban.ski/aggregations-the-elasticsearch-group-by.html
Logging and ranting / Vytis Valentinavičius (Lamoda)Ontico
HighLoad++ 2017
Зал «Пекин+Шанхай», 7 ноября, 16:00
Тезисы:
http://www.highload.ru/2017/abstracts/2842.html
A story about real life experience in Lamoda, featuring logging, forest animals, limited size buffers and morning routines.
Possible takeaways from this presentation:
1. Understanding the need of central log aggregation
2. Learning a few tips about logging and event aggregation
3. Saving a lot of money by implementing your own personal "poor-man's" NewRelic
...
Precog & MongoDB User Group: Skyrocket Your Analytics MongoDB
earn how to do advanced analytics with the Precog data science platform on your MongoDB database. It's free to download the Precog file and after installing, you'll be on your way to analyzing all the data in your MongoDB database, without forcing you to export data into another tool or write any custom code. Learn more here: www.precog.com/mongodb
Presentation held during SFScon15 - Free Software Conference, 13.11.2015 @ TIS innovation park, Bolzano
--
Most developers use databases to support their projects. However, database systems are normally seen as a “black box” to which a developer passes a query in order to get data.
This talk gives some insights in how a query is processed inside PostgreSQL. It provides a step-by-step walk through the different stages of the database backend. It starts with the analysis of the query syntax, explains the planning of the query execution, and finally shows how the result is retrieved.
If you got hungry for more, have a look at the more detailed workshop that follows.
This talk moves beyond the standard introduction into Elasticsearch and focuses on how Elasticsearch tries to fulfill its near-realtime contract. Specifically, I’ll show how Elasticsearch manages to be incredibly fast while handling huge amounts of data. After a quick introduction, we will walk through several search features and how the user can get the most out of the Elasticsearch. This talk will go under the hood exploring features like search, aggregations, highlighting, (non-)use of probabilistic data structures and more.
OSMC 2014: Introduction into collectd | Florian FosterNETWAYS
Periodically measuring performance metrics of production systems allows administrators and developers to analyze system behavior during and after outages, quantify performance improvements, and detect trends and take proactive measures before problems arise. Performance metrics are also interesting for alerting, because they can be aggregated meaningfully, thereby basing an alert on a group of hosts rather than each host individually, for example.
This talk will give an introduction to collectd, an open-source tool to gather, process and store performance metrics. A sample setup which aggregates a couple of metrics and stores the aggregate in Graphite will be presented. Afterwards, we will show how the collectd-nagios utility can be used to define alerts in Icinga based on this data.
PCU@RISE 2017 - Building a thesaurus for product searchPCU Consortium
In the field of ecommerce, search is very important, but very specific. Smile provides in Magento Elastic Suite a thesaurus that addresses these specificities, and aims at enhancing it with Machine Learning in its new PCU R&D projects along with its partners.
PCU@RISE 2017 - Building a thesaurus for product searchMarc Dutoo
In the field of ecommerce, search is very important, but very specific. Smile provides in Magento Elastic Suite a thesaurus that addresses these specificities, and aims at enhancing it with Machine Learning in its new PCU R&D projects along with its partners.
Smart solutions for productivity gain IQA conference 2017Steve Franklin
Presentation by Steve Franklin of Cement & Aggregate Consulting at the 2017 IQA conference in Toowoomba covering use of drones and quarry planning and scheduling tools.
This presentation will demonstrate how you can use the aggregation pipeline with MongoDB similar to how you would use GROUP BY in SQL and the new stage operators coming 3.4. MongoDB’s Aggregation Framework has many operators that give you the ability to get more value out of your data, discover usage patterns within your data, or use the Aggregation Framework to power your application. Considerations regarding version, indexing, operators, and saving the output will be reviewed.
OSMC 2018 | Learnings, patterns and Uber’s metrics platform M3, open sourced ...NETWAYS
At Uber we use high cardinality monitoring to observe and detect issues with our 4,000 microservices running on Mesos and across our infrastructure systems and servers. We’ll cover how we put the resulting 6 billion plus time series to work in a variety of different ways, auto-discovering services and their usage of other systems at Uber, setting up and tearing down alerts automatically for services, sending smart alert notifications that rollup different failures into individual high level contextual alerts, and more. We’ll also talk about how we accomplish all this with a global view of our systems with M3, our open source metrics platform. We’ll take a deep dive look at how we use M3DB, now available as an open source Prometheus long term storage backend, to horizontally scale our metrics platform in a cost efficient manner with a system that’s still sane to operate with petabytes of metrics data.
The 'macro view' on Big Query:
We started with an overview, some typical uses and moved to project hierarchy, access control and security.
In the end we touch about tools and demos.
Similar to Elasticsearch: Getting Started Part 3 Aggregations (20)
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
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Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
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A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
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Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
2. Kloojj.com
Suyog Dilip Kale
Technology Evangelist
Chief Architect
www.kloojj.com
Organiser
Pune Developer’s Community
www.meetup.com/Pune-Developers-Community
http://www.punedevscommunity.in/
3. Kloojj.com
● Aggregations
○ What is aggregations in Elasticsearch?
○ Metrics aggregations
■ Avg aggregation
■ Cardinality aggregation
■ Extended stats aggregation
■ Min & Max aggregation
■ Sum aggregation
○ Bucket aggregations
○ Nested Bucket aggregations
4. Kloojj.com
● Read-What is aggregations in Elasticsearch
○ Aggregations helps provide aggregated data based on a search query.
○ It can be composed in order to build complex summaries of the data.
○ There are many different types of aggregations, each with its own
purpose and output.
○ Elasticsearch aggregations let you zoom out to explore trends and
patterns in your data.
○ What if your ecommerce portal has billions of user visits and you
want drill down it by country, states and then cities? What if you want
to see avg user age groups OR gender wise product interests ? What if
you want calculate daily, weekly or monthly sales ?
○ Everything is much easy with Elasticsearch aggregations
5. Kloojj.com
● Read-Metrics aggregations
○ Metrics Aggregations are used to compute metrics over set of
documents. Numeric matrices are either single-valued like average
aggregation or multi-valued like stats.
○ Avg aggregations: to get the average of any numeric field present in
the aggregated documents, see below example:
GET /website/user/_search
{
"aggs": {
"avg_score": {
"avg": {
"field": "score"
}
}
}
}
6. Kloojj.com
● Read-Metrics aggregations
○ Cardinality aggregations: to get the count of distinct values of a
particular field, see below example:
GET /website/user/_search
{
"aggs": {
"cardinality_cname": {
"cardinality": {
"field": "cname"
}
}
}
}
○ This will give you distinct country name count.
7. Kloojj.com
● Read-Metrics aggregations
○ Extended stats aggregations: it generates all the statistics about a
specific numerical field in aggregated documents, for example:
GET /website/user/_search
{
"aggs": {
"stats_score": {
"stats": {
"field": "score"
}
}
}
}
○ It will return all statistics on score field like total records,minimum,
maximum, average and total sum value.
8. Kloojj.com
● Read-Metrics aggregations
○ Min & Max aggregations: These aggregations can be used to find the
max or min value of a specific numeric field in aggregated documents.
For example below one returns max value from score field:
GET /website/user/_search
{
"aggs": {
"max_score": {
"max": {
"field": "score"
}
}
}
}
9. Kloojj.com
● Read-Metrics aggregations
○ Sum aggregation: This aggregation calculates the sum of a specific
numeric field in aggregated documents. For example:
GET /website/user/_search
{
"aggs": {
"total_score": {
"sum": {
"field": "score"
}
}
}
}
○ This returns the total of score value
10. Kloojj.com
● Read-Bucket aggregations
○ These aggregations contain many buckets for different types of
aggregations having a criterion, which determines whether a
document belongs to that bucket or not.
○ There are many other special bucket aggregations, those are −
● Date Histogram Aggregation
● Date Range Aggregation
● Filter Aggregation
● Filters Aggregation
● Geo Distance Aggregation
● GeoHash grid Aggregation
● Global Aggregation
● Histogram Aggregation
● IPv4 Range Aggregation
● Missing Aggregation
● Nested Aggregation
● Range Aggregation
● Reverse nested Aggregation
● Sampler Aggregation
● Significant Terms Aggregation
● Terms Aggregation
11. Kloojj.com
● Read-Bucket aggregations
○ Let’s try term bucket aggregation
GET /website/user/_search
{
"aggs": {
"by_cname": {
"terms": {
"field": "cname"
}
}
}
}
○ If you see the result it will return the document counts for each
country found in aggregated documents
12. Kloojj.com
● Read-Nested Bucket aggregations
○ To drill down the aggregation results, it is best way to nest them, for
example, if you want to get counts against each action by country try
below query:
GET /website/user/_search
{
"aggs": {
"by_cname": {
"terms": {
"field": "cname"
},
"aggs": {
"by_action": {
"terms": {
"field": "action"
}
}
}
}
}
}