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Event

Elastic Berlin Meetup @ Zalando: October Edition

2024-10-15 – 2024-10-15 Meetup Visit website ↗

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We're back with another meetup at Zalando!

Please make sure to provide your first name and last name as this will be required by security to enter the meetup.

Address: Zalando BHQ-X, Valeska-Gert-Straße 5, 10243 Berlin

Agenda: 18.00: Doors open 18.10: Execution in a Vectorized Query Engine 18.40: Break with pizza and drinks 19.00: Open source observability with OpenTelemetry and Elasticsearch 19.30: Evaluating Elasticsearch Nearest Neighbour Search for E-Commerce 20.00: Networking 20.30: Close

Talks: Execution in a Vectorized Query Engine ES\|QL is a new piped query language for Elasticsearch. It supports writing composable queries and it features a multi-staged execution. Unlike the other languages supported by Elasticsearch\, ES\|QL doesn't transpile to Query DSL or use the internal search client: it's based on its own stack. This comes with a sophisticated query analysis and optimisation steps\, as well as parallelisation and vectorisation. This talk will give an overview of the execution flow of a query and touch on a few key implementation aspects\, following the query from its first syntactic analysis down to Lucene delegation followed by returning the results back to the user\, all in a distributed environment.

Bogdan Pintea (Senior Software Engineer @ Elastic)

Open source observability with OpenTelemetry and Elasticsearch Recognized by Gartner as a leading observability tool, Elasticsearch is not just log analytics. It has infrastructure monitoring, alerts, APM capabilities - and it's all open-source!

Now with the addition of OpenTelemetry, it's even easier to onboard your telemetry data in a standard and vendor-neutral way. Join Andrzej in a technical session to discover the shortest path from zero to a fully functional open-source observability solution with the OTEK stack - OpenTelemetry, Elasticsearch and Kibana.

Andrzej Stencel - (Senior Software Engineer @ Elastic)

Evaluating Elasticsearch Nearest Neighbour Search for E-Commerce Experiments to analyze the utility, efficiency and effectiveness of brute force k nearest neighbor and approximate nearest neighbor algorithms available in Elasticsearch to enable Zalando's search, browse and fashion assistant capabilities.

Girish Chandrasheka (Zalando)

Sessions & talks

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Evaluating Elasticsearch Nearest Neighbour Search for E-Commerce

2024-10-15

talk

elasticsearch nearest neighbor search knn brute force approximate nearest neighbor

Experiments to analyze the utility, efficiency and effectiveness of brute force k nearest neighbor and approximate nearest neighbor algorithms available in Elasticsearch to enable Zalando's search, browse and fashion assistant capabilities.

Open source observability with OpenTelemetry and Elasticsearch

2024-10-15

talk

Andrzej Stencel (Elastic)

opentelemetry elasticsearch Kibana

Recognized by Gartner as a leading observability tool, Elasticsearch is not just log analytics. It has infrastructure monitoring, alerts, APM capabilities—and it's all open-source! Now with the addition of OpenTelemetry, it's even easier to onboard your telemetry data in a standard and vendor-neutral way. Join Andrzej in a technical session to discover the shortest path from zero to a fully functional open-source observability solution with the OTEK stack - OpenTelemetry, Elasticsearch and Kibana.

Execution in a Vectorized Query Engine

2024-10-15

talk

Bogdan Pintea (Elastic)

elasticsearch es|ql lucene vectorisation distributed query execution

ES|QL is a new piped query language for Elasticsearch. It supports writing composable queries and it features a multi-staged execution. Unlike the other languages supported by Elasticsearch, ES|QL doesn't transpile to Query DSL or use the internal search client: it's based on its own stack. This comes with a sophisticated query analysis and optimisation steps, as well as parallelisation and vectorisation. This talk will give an overview of the execution flow of a query and touch on a few key implementation aspects, following the query from its first syntactic analysis down to Lucene delegation followed by returning the results back to the user, all in a distributed environment.