2) Announcer should actually delete its zk entries when it is told to unannounce something
3) Skip over complex columns that we don't have a proper deserializer for
of single-segment realtime tasks.
Realtime:
- Move firehose stuff to com.metamx.druid.realtime.firehose package
- ClippedFirehoseFactory provides a time-clipped view
- TimedShutoffFirehoseFactory shuts off at a particular time
Indexer:
- Split StringInputRowParser into {String,Map}InputRowParser
Merger:
- Remove minTime in favor of clipped firehoses
- Add task executor servlet that can push events to EventReceivers
- Add EventReceivingFirehose that accepts events as an EventReceiver
2) Fix bug with IndexMerger and null columns
3) Add QueryableIndexIndexableAdapter so that QueryableIndexes can be merged
4) Adjust twitter example to have multiple values for each hash tag
5) Adjusted GroupByQueryEngine to just drop dimensions that don't exist instead of throwing an NPE
2) Create SegmentLoader interface for the loading of segments!
3) Setup serialization of new format and conversion function inside IndexIO
4) Make some adjustments to the twitter demo to make it make a bit more sense based on some email feedback from someone kicking the tires.
2) Add GroupByTimeseriesQueryRunnerTest which wraps a GroupByQueryRunner to look like a TimeseriesQueryRunner and leverages the tests there to help verify behavior (#8)
2) Add some docs to InputRow/Row to indicate that column names passed into the methods are *always* lowercase and that the rows need to act accordingly. (fixes#29, or at least clarifies the behavior...)
2) Rename ServerMain to ComputeMain
3) Refactor ComputeMain to ComputeMain and ComputeNode to allow for extensions
4) Remove "TheSizeAdjuster", was old legacy stuff that's not relevant anymore
5) Fix bug with registering different IndexIO handlers
6) Adjust it so that when a query type is unknown, it returns an error message instead of just emitting an alert and returning nothing
7) Create super classes for the various *Node classes that allow for code sharing on pieces that are common
