July 15, 2015 Leave a comment
For those of you interested in some comprehensive Solr training taught by an expert from Sematext who knows it inside and out, we’re running a super hands-on training workshop in New York City from October 19-20.
Developers and Devops who want to configure, tune and manage Solr at scale.
What you’ll get out of it:
In two days of training Rafal will help:
- bring Solr novices to the level where he/she would be comfortable with taking Solr to production
- give experienced Solr users proven and practical advice based on years of experience designing, tuning, and operating numerous Solr clusters to help with their most advanced and pressing issues
* See the Course Outline at the bottom of this post for details
When & Where:
- Dates: October 19 & 20 (Monday & Tuesday)
- Time: 9:00 a.m. — 5:00 p.m.
- Location: New Horizons Computer Learning Center in Midtown Manhattan (map)
- Cost: $1,200 “early bird rate” (valid through September 1) and $1,500 afterward. And…we’re also offering a 50% discount for the purchase of a 2nd seat!
- Food/Drinks: Light breakfast and lunch will be provided
Attendees will go through several sequences of short lectures followed by interactive, group, hands-on exercises. There will be a Q&A session after each such lecture-practicum block.
Got any questions or suggestions for the course? Just drop us a line or hit us @sematext!
Lastly, if you can’t make it…watch this space or follow @sematext — we’ll be adding more Solr training workshops in the US, Europe and possibly other locations in the coming months. We are also known worldwide for our Solr Consulting Services and Solr Production Support.
Hope to see you in the Big Apple in October!
Solr Training Workshop – Course Outline
- Introduction to Solr
- What is Solr and use – cases
- Solr master – slave architecture
- SolrCloud architecture
- Why & When SolrCloud
- Solr master – slave vs SolrCloud
- Starting Solr with schema-less configuration
- Indexing documents
- Retrieving documents using URI request
- Deleting documents
- Indexing data