Skip to content
Eindex is a module for sharding column based indexes in Cassandra.
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
src
.gitignore
LICENSE.txt
README.md
pom.xml

README.md

Earnstone Sharded Column Index for Cassandra

Description

Eindex is a module for sharding column based indexes. With a similar scheme of how Cassandra shards row keys we decided to shard column keys. With this scheme you can still use the Cassandra Random Partitioner and get range queries for keys. Our goal is to support 100's of millions of keys across a Cassandra cluster.

Download

earnstone-index-0.1-all.zip

How it Works

For the simple case lets consider the index keys to be uniquie (or mostly unique) and the value for each key is 1000 + key. Lets say we want to index the evens list 2, 4, 6, 8, 10, ... 100 plus lets throw in one odd 19.
Lets set the shard boundries to 20, 40, 60, 80, 100. The indexer will have the shard boundries loaded into memory (first constraint). When we lookup the index '19' we first lookup it's shard boundry in this case it would be 20.
given that boundry we then lookup the Cassandra row key 'myIndex:20' and column key '19' which will yeild the value of '1019'. Since the shard boundries are cached this equates to only 1 Cassandra query. We can also range query. Lets say we are looking for the index '17', which doesn't exist and we want the next 5 indexes. We could call getValueRangesForIndex with and index value of '17' and a limit of 5 will return [18, 1018], [19, 1019], [20, 1020], [22, 1022], [24, 1024] or all the evens plus the 19 we added earlier. The indexer will look at the next shard to fulfill the requested limit if needed. So in this example it quiered Cassandra row key 'myindex:20' and retrieve 18, 19 then queries the next shard boundry key 'myindex:40' to retrieve the next keys of 20, 22, 24. You can also reverse the range query so running the same query will yeild [16, 1016], [14, 1014], [12, 1012], [10, 1010], [8, 1008]. Each of these range queries translated into 2 Cassrandra row reads. So when you query close to a broundry it might translate into 2 queries to Cassandra.

What happens when you store more than 1 value per index? It gets written into another Cassandra row key. So lets store the value '1000' into the exiting key of [19, 1019]. When more that one value is written to the same index key a special empty marker is place at the Cassandra row key 'myindex:20' column '19'. The values are written into a new Cassandra row key 'myindex::19' column values '1019, 1000' (Notice the '::' deferiantes the shard keys from actual index keys). So if we run the same range scan of '17' and limit 5 we get [18, 1018], [19, [1000, 1019]] ... Notice the value keys come back sorted. This query will tranluate into 3 cassandra queries. Each index key that has multiple values will transulate into another Cassandra query. There is an optimization where if the index key has only 1 value (like a primary key) then there isn't any extra query to Cassandra.

Notes and Limitations

  • The automated sharding isn't complete. You must prepopulate the shards by calling initializeShardBoundries.
  • Currently the index keys and index values must be of the same type because they will be persisted into the same column family. With little modification we should be able to support things like Long indexes with UUIDs or Strings as values. Or even String indexes to Long valuesm but mis-matching types will require 2 column families. Currently multiple indexes of the same type can be stored in the same column family.
  • The index performs best if the keys are considered to be mostly unique. Things like geo-location data where it would be rare to have the exact same GPS coords would work great. There is an optimization for keys that only have 1 value where no extra querying has to be performed. If a key contains multiple values then for each key in your range scan that has multiple-values will transulate into multiple queries.
  • The shard boundries are currently constrainted by memory. A basic rule of thumb we use is for every shard to have a capacity of 100,000 columns. So 1000 boundries held in memory X 100K columns is 100M indexes. Or a better way to say it is for every 1K of boundries in memory = 100M indexes in Cassandra.
  • To fulfill range query requests the algorithm only looks at 1 addition shard (this might change depending on needs). So if the current shard and the next shard have less than the limit you quieried for then you will not get back a full limit of keys.
You can’t perform that action at this time.