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some minor doc changes

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Robin 2016-01-29 11:43:01 -06:00
parent 08802c345d
commit 1d57e3267d
3 changed files with 9 additions and 9 deletions
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4
docs/content/configuration/index.md
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@ -140,8 +140,8 @@ The Druid servers emit various metrics and alerts via something we call an Emitt
|Property|Description|Default|
|--------|-----------|-------|
|`druid.emitter.http.timeOut`|The timeout for data reads.|PT5M|
|`druid.emitter.http.flushMillis`|How often to internal message buffer is flushed (data is sent).|60000|
|`druid.emitter.http.flushCount`|How many messages can the internal message buffer hold before flushing (sending).|500|
|`druid.emitter.http.flushMillis`|How often the internal message buffer is flushed (data is sent).|60000|
|`druid.emitter.http.flushCount`|How many messages the internal message buffer can hold before flushing (sending).|500|
|`druid.emitter.http.recipientBaseUrl`|The base URL to emit messages to. Druid will POST JSON to be consumed at the HTTP endpoint specified by this property.|none|
#### Composing Emitter Module

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docs/content/development/datasketches-aggregators.md
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@ -4,8 +4,8 @@ layout: doc_page
## DataSketches aggregator
Druid aggregators based on [datasketches](http://datasketches.github.io/) library. Note that sketch algorithms are approxiate, see details in the "Accuracy" section of the datasketches doc.
At ingestion time, this aggregator creates the theta sketch objects which get stored in Druid segments. Logically speaking, a theta sketch object can be thought of as a Set data structure. At query time, sketches are read and aggregated(set unioned) together. In the end, by default, you receive the estimate of number of unique entries in the sketch object. Also, You can use post aggregators to do union, intersection or difference on sketch columns in the same row.
Druid aggregators based on [datasketches](http://datasketches.github.io/) library. Note that sketch algorithms are approximate; see details in the "Accuracy" section of the datasketches doc.
At ingestion time, this aggregator creates the theta sketch objects which get stored in Druid segments. Logically speaking, a theta sketch object can be thought of as a Set data structure. At query time, sketches are read and aggregated (set unioned) together. In the end, by default, you receive the estimate of the number of unique entries in the sketch object. Also, you can use post aggregators to do union, intersection or difference on sketch columns in the same row.
Note that you can use `thetaSketch` aggregator on columns which were not ingested using same, it will return estimated cardinality of the column. It is recommended to use it at ingestion time as well to make querying faster.
### Aggregators

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docs/content/ingestion/batch-ingestion.md
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@ -151,16 +151,16 @@ The tuningConfig is optional and default parameters will be used if no tuningCon
|Field|Type|Description|Required|
|-----|----|-----------|--------|
|workingPath|String|the working path to use for intermediate results (results between Hadoop jobs).|no (default == '/tmp/druid-indexing')|
|workingPath|String|The working path to use for intermediate results (results between Hadoop jobs).|no (default == '/tmp/druid-indexing')|
|version|String|The version of created segments.|no (default == datetime that indexing starts at)|
|leaveIntermediate|Boolean|leave behind files in the workingPath when job completes or fails (debugging tool).|no (default == false)|
|partitionsSpec|Object|a specification of how to partition each time bucket into segments, absence of this property means no partitioning will occur.More details below.|no (default == 'hashed'|
|partitionsSpec|Object|A specification of how to partition each time bucket into segments, absence of this property means no partitioning will occur.More details below.|no (default == 'hashed')|
|maxRowsInMemory|Integer|The number of rows to aggregate before persisting. This number is the post-aggregation rows, so it is not equivalent to the number of input events, but the number of aggregated rows that those events result in. This is used to manage the required JVM heap size.|no (default == 5 million)|
|cleanupOnFailure|Boolean|Cleans up intermediate files when the job fails as opposed to leaving them around for debugging.|no (default == true)|
|leaveIntermediate|Boolean|Leave behind intermediate files (for debugging) in the workingPath when a job completes, whether it passes or fails.|no (default == false)|
|cleanupOnFailure|Boolean|Clean up intermediate files when a job fails (unless leaveIntermediate is on).|no (default == true)|
|overwriteFiles|Boolean|Override existing files found during indexing.|no (default == false)|
|ignoreInvalidRows|Boolean|Ignore rows found to have problems.|no (default == false)|
|useCombiner|Boolean|Use hadoop combiner to merge rows at mapper if possible.|no (default == false)|
|jobProperties|Object|a map of properties to add to the Hadoop job configuration.|no (default == null)|
|jobProperties|Object|A map of properties to add to the Hadoop job configuration.|no (default == null)|
|buildV9Directly|Boolean|Whether to build v9 index directly instead of building v8 index and convert it to v9 format|no (default = false)|
|numBackgroundPersistThreads|Integer|The number of new background threads to use for incremental persists. Using this feature causes a notable increase in memory pressure and cpu usage, but will make the job finish more quickly. If changing from the default of 0 (use current thread for persists), we recommend setting it to 1.|no (default == 0)|