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www.webLyzard.com
webLyzard Web Intelligence and Visual Analytics
Elasticsearch Meetup
Arno Scharl, Alexander Hubmann-Haidvogel
2
UNEP Live Web
Intelligence
uneplive.unep.org
Developed by the Department of New Media Technology of
MODUL University Vienna and powered by webLyzard technology
www.weblyzard.com/unep-live ▪ unep.ecoresearch.net
3
4
5 Elasticsearch | Integration
History
- Started with PostgreSQL/Tsearch2
- Switched to Apache Lucene in 2009
- Adopted Elasticsearch 1.0 early 2014
- Migrated to Elasticsearch 6 earlier this year (currently 6.5.1)
Current Cluster
- 5 physical machines (XEON E5, 40 cores, 256GB RAM)
- 3 x 2TB M.2 NVMe Samsung 960 Pro in striped LVM
- Multiple Elasticsearch nodes per machine
4 data nodes, separate master nodes, one coordinating-only node per machine
- Docker containers, overlay network, discovery using DNS
6 Elasticsearch | Integration
Indexing
– Custom component based on Vert.x
– Data read from PostgreSQL
– Indexer applies transformations/de-normalizations
– Enriches with additional metadata; e.g., translations
– One index per source and language (e.g. German news media)
per month (e.g. de.1.media.2018-12)
– Balance between index/shard size and number of indexes
affected by queries and aggregations
7 Elasticsearch | Integration
Migration 1.7 > 6.x
– No in-place upgrade path from Elasticsearch 1.x to 6.x
– Skipped Elasticsearch 2.x because of field names containing
dots in existing mapping
– Complete re-index needed, adapted document mapping
Performance Improvements
– Single request performance improved by about 50%
– Concurrent requests with 100 simulated users improved
by almost 85%
8 Elasticsearch | Integration
Example 1: Geographic Map
– Hashgrid aggregation for extracted target locations
– User-selectable precision
– Aggregate average document sentiment
Example 2: Word Tree
– Inner hits on search query
– Filtered for sentences matching the query
– Maintaining document-level sorting
9
10 InVID | www.weblyzard.com/invid
In Video Veritas – Video Verification
Media Partners: APA, AFP, Deutsche Welle
EU Horizon 2020, 3.65 Mio EUR
SONAR | www.weblyzard.com/sonar
Semantic Repository for News Analytics
Media Partner: ProSiebenSat.1 PULS 4
Google News Initiative, 225,000 EUR
ReTV | www.weblyzard.com/retv
Enhancing and Repurposing TV Content
Media Partners: Zattoo, rbb|24, Sound & Vision
EU Horizon 2020, 3.5 Mio EUR
11 EPOCH | www.weblyzard.com/epoch
Extracting and Predicting Events from Online
Communication and Hybrid Datasets
Partners: Ketchum Publico, KPMG
FFG ICT of the Future; 500,000 EUR
EPOCH will assess the real-world impact of events reported
in news and social media channels. It will use extracted
knowledge from the public debate across these channels to
predict future trends, offering a visual dashboard to explore
and analyze these trends.
Organizations will be able to identify and thus better
prepare for anticipated changes, adapting their decision-
making and resource allocation strategies accordingly. New
methods developed witin EPOCH will be applied to the
domains of purchase price forecasting and public relations.
12
@weblyzard
We Are Definitely Hiring
Our team spans 2+ countries and counting.
See if you or someone you know is a fit.
careers@weblyzard.com

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Elasticsearch Meetup Vienna - webLyzard Live Demo

  • 1. 1 www.webLyzard.com webLyzard Web Intelligence and Visual Analytics Elasticsearch Meetup Arno Scharl, Alexander Hubmann-Haidvogel
  • 2. 2 UNEP Live Web Intelligence uneplive.unep.org Developed by the Department of New Media Technology of MODUL University Vienna and powered by webLyzard technology www.weblyzard.com/unep-live ▪ unep.ecoresearch.net
  • 3. 3
  • 4. 4
  • 5. 5 Elasticsearch | Integration History - Started with PostgreSQL/Tsearch2 - Switched to Apache Lucene in 2009 - Adopted Elasticsearch 1.0 early 2014 - Migrated to Elasticsearch 6 earlier this year (currently 6.5.1) Current Cluster - 5 physical machines (XEON E5, 40 cores, 256GB RAM) - 3 x 2TB M.2 NVMe Samsung 960 Pro in striped LVM - Multiple Elasticsearch nodes per machine 4 data nodes, separate master nodes, one coordinating-only node per machine - Docker containers, overlay network, discovery using DNS
  • 6. 6 Elasticsearch | Integration Indexing – Custom component based on Vert.x – Data read from PostgreSQL – Indexer applies transformations/de-normalizations – Enriches with additional metadata; e.g., translations – One index per source and language (e.g. German news media) per month (e.g. de.1.media.2018-12) – Balance between index/shard size and number of indexes affected by queries and aggregations
  • 7. 7 Elasticsearch | Integration Migration 1.7 > 6.x – No in-place upgrade path from Elasticsearch 1.x to 6.x – Skipped Elasticsearch 2.x because of field names containing dots in existing mapping – Complete re-index needed, adapted document mapping Performance Improvements – Single request performance improved by about 50% – Concurrent requests with 100 simulated users improved by almost 85%
  • 8. 8 Elasticsearch | Integration Example 1: Geographic Map – Hashgrid aggregation for extracted target locations – User-selectable precision – Aggregate average document sentiment Example 2: Word Tree – Inner hits on search query – Filtered for sentences matching the query – Maintaining document-level sorting
  • 9. 9
  • 10. 10 InVID | www.weblyzard.com/invid In Video Veritas – Video Verification Media Partners: APA, AFP, Deutsche Welle EU Horizon 2020, 3.65 Mio EUR SONAR | www.weblyzard.com/sonar Semantic Repository for News Analytics Media Partner: ProSiebenSat.1 PULS 4 Google News Initiative, 225,000 EUR ReTV | www.weblyzard.com/retv Enhancing and Repurposing TV Content Media Partners: Zattoo, rbb|24, Sound & Vision EU Horizon 2020, 3.5 Mio EUR
  • 11. 11 EPOCH | www.weblyzard.com/epoch Extracting and Predicting Events from Online Communication and Hybrid Datasets Partners: Ketchum Publico, KPMG FFG ICT of the Future; 500,000 EUR EPOCH will assess the real-world impact of events reported in news and social media channels. It will use extracted knowledge from the public debate across these channels to predict future trends, offering a visual dashboard to explore and analyze these trends. Organizations will be able to identify and thus better prepare for anticipated changes, adapting their decision- making and resource allocation strategies accordingly. New methods developed witin EPOCH will be applied to the domains of purchase price forecasting and public relations.
  • 12. 12 @weblyzard We Are Definitely Hiring Our team spans 2+ countries and counting. See if you or someone you know is a fit. careers@weblyzard.com