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Version 1.0
Lucene Based Indexes on Cassandra
An Anant Corporation Story.
Types Covered + Pros and Cons
● Packaged
● DIY
● Pros
● Cons
Packaged
DSE Search / Solr
● https://docs.datastax.com/en/dse/6.0/dse-dev/datastax_enterprise/search
/searchTOC.html
Cassandra Lucene Index
● instaclustr/cassandra-lucene-index: Lucene based secondary indexes for
Cassandra
a. https://github.com/instaclustr/cassandra-lucene-index
● Mutations to Cassandra -> Mutations on Disk (for that node)
Elessandra / ElasticSearch
● strapdata/elassandra: Elassandra = Elasticsearch + Apache Cassandra
a. https://github.com/strapdata/elassandra
● Cassandra + Elasticsearch
a. Mutations to Cassandra -> Mutations to Elasticsearch
DIY
Event -> CQRS -> Cassandra + Index
● Write
○ Event / Command goes into an Event Source repository (Kafka, SQL
Table, etc. )
○ Command Processor processes it into CQL / Elasticsearch or SOLR or
Amazon ... Algolia
● Request
○ Event / Command goes into an Event Source repository (Kafka, SQL
Table, etc. )
○ Command Processor goes to index / finds the data, goes to Cassandra ,
gets the data, returns.
○ Query the index --
Cassandra -> Batch -> Index
● Writes to Cassandra
● Every now and then - Index to ???
● Cassandra + Spark
Cassandra Triggers -> Index
Serverless Function -> Cassandra + Index
Apache Nifi (Lucene) -> Nifi Processor -> Cassandra + Index
Pros
● extremely rich search capabilities
● Geospatial
● synonym
● fuzzy logic search
● Typos
● Stemming
● packaged elastic/solr/lucene -> shorter latency
● separate index -> better separation of concerns and speed
Cons
● pure lucene -> reinventing the wheel of what Solr/ElasticSearch
● external elastic/solr/ ?? -> longer latency between finding the data / getting
the data
● packaged elastic/solr/lucene -> don't expect it to solve all your problems
● consistency issues (if DIY)
● lucene is memory heavy
● lucene is disk heavy
Strategy: Scalable Fast Data
Architecture: Cassandra, Spark, Kafka
Engineering: Node, Python, JVM,CLR
Operations: Cloud, Container
Rescue: Downtime!! I need help.
 www.anant.us | solutions@anant.us | (855) 262-6826
3 Washington Circle, NW | Suite 301 | Washington, DC 20037
Resources
● tjake/Solandra: Solandra = Solr + Cassandra

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Cassandra Lunch #23: Lucene Based Indexes on Cassandra

  • 1. Version 1.0 Lucene Based Indexes on Cassandra An Anant Corporation Story.
  • 2. Types Covered + Pros and Cons ● Packaged ● DIY ● Pros ● Cons
  • 4. DSE Search / Solr ● https://docs.datastax.com/en/dse/6.0/dse-dev/datastax_enterprise/search /searchTOC.html
  • 5. Cassandra Lucene Index ● instaclustr/cassandra-lucene-index: Lucene based secondary indexes for Cassandra a. https://github.com/instaclustr/cassandra-lucene-index ● Mutations to Cassandra -> Mutations on Disk (for that node)
  • 6. Elessandra / ElasticSearch ● strapdata/elassandra: Elassandra = Elasticsearch + Apache Cassandra a. https://github.com/strapdata/elassandra ● Cassandra + Elasticsearch a. Mutations to Cassandra -> Mutations to Elasticsearch
  • 7. DIY
  • 8. Event -> CQRS -> Cassandra + Index ● Write ○ Event / Command goes into an Event Source repository (Kafka, SQL Table, etc. ) ○ Command Processor processes it into CQL / Elasticsearch or SOLR or Amazon ... Algolia ● Request ○ Event / Command goes into an Event Source repository (Kafka, SQL Table, etc. ) ○ Command Processor goes to index / finds the data, goes to Cassandra , gets the data, returns. ○ Query the index --
  • 9. Cassandra -> Batch -> Index ● Writes to Cassandra ● Every now and then - Index to ??? ● Cassandra + Spark
  • 11. Serverless Function -> Cassandra + Index
  • 12. Apache Nifi (Lucene) -> Nifi Processor -> Cassandra + Index
  • 13. Pros ● extremely rich search capabilities ● Geospatial ● synonym ● fuzzy logic search ● Typos ● Stemming ● packaged elastic/solr/lucene -> shorter latency ● separate index -> better separation of concerns and speed
  • 14. Cons ● pure lucene -> reinventing the wheel of what Solr/ElasticSearch ● external elastic/solr/ ?? -> longer latency between finding the data / getting the data ● packaged elastic/solr/lucene -> don't expect it to solve all your problems ● consistency issues (if DIY) ● lucene is memory heavy ● lucene is disk heavy
  • 15. Strategy: Scalable Fast Data Architecture: Cassandra, Spark, Kafka Engineering: Node, Python, JVM,CLR Operations: Cloud, Container Rescue: Downtime!! I need help.  www.anant.us | solutions@anant.us | (855) 262-6826 3 Washington Circle, NW | Suite 301 | Washington, DC 20037