本篇文章为你整理了GroupBy · ApacheDruid中文技术文档（group by distribute by）的详细内容，包含有group by shop group by distribute by group by案例 groupby使用方法 GroupBy · ApacheDruid中文技术文档，希望能帮助你了解 GroupBy · ApacheDruid中文技术文档。
dimensions : [ country , device ],
limitSpec : { type : default , limit : 5000, columns : [ country , data_transfer ] },
filter : {
type : and ,
fields : [
{ type : selector , dimension : carrier , value : AT T },
{ type : or ,
fields : [
{ type : selector , dimension : make , value : Apple },
{ type : selector , dimension : make , value : Samsung }
aggregations : [
{ type : longSum , name : total_usage , fieldName : user_count },
{ type : doubleSum , name : data_transfer , fieldName : data_transfer }
postAggregations : [
{ type : arithmetic ,
name : avg_usage ,
fn : / ,
fields : [
{ type : fieldAccess , fieldName : data_transfer },
{ type : fieldAccess , fieldName : total_usage }
intervals : [ 2012-01-01T00:00:00.000/2012-01-03T00:00:00.000 ],
having : {
type : greaterThan ,
aggregation : total_usage ,
value : 100
GroupBy
n*m 5000 n country m device 2012-01-01 2012-01-03 sample_datasource 100 longSum total_usage country device double total_usage data_transfer
[
version : v1 ,
timestamp : 2012-01-01T00:00:00.000Z ,
event : {
country : some_dim_value_one ,
device : some_dim_value_two ,
total_usage : some_value_one ,
data_transfer : some_value_two ,
avg_usage : some_avg_usage_value
version : v1 ,
timestamp : 2012-01-01T00:00:12.000Z ,
event : {
dim1 : some_other_dim_value_one ,
dim2 : some_other_dim_value_two ,
sample_name1 : some_other_value_one ,
sample_name2 : some_other_value_two ,
avg_usage : some_other_avg_usage_value
GroupBy
GroupBy t1 t3 tags GroupBy row1 t1 t2 t3 dimensionSpec,
subtotalSpec
subtotalsSpec dimensions outputName dimensions groupBy
{
type : groupBy ,
dimensions : [
type : default ,
dimension : d1col ,
outputName : D1
type : extraction ,
dimension : d2col ,
outputName : D2 ,
extractionFn : extraction_func
type : lookup ,
dimension : d3col ,
outputName : D3 ,
name : my_lookup
subtotalsSpec :[ [ D1 , D2 , D3 ], [ D1 , D3 ], [ D3 ]],
dimensions [ D1 D2 D3 ] [ D1 D3 ] [ D3 ] 3 groupBy DimensionSpec :
[
version : v1 ,
timestamp : t1 ,
event : { D1 : .. , D2 : .. , D3 : .. }
version : v1 ,
timestamp : t2 ,
event : { D1 : .. , D2 : .. , D3 : .. }
version : v1 ,
timestamp : t1 ,
event : { D1 : .. , D3 : .. }
version : v1 ,
timestamp : t2 ,
event : { D1 : .. , D3 : .. }
version : v1 ,
timestamp : t1 ,
event : { D3 : .. }
version : v1 ,
timestamp : t2 ,
event : { D3 : .. }
v2 , Broker Broker N-way Broker
v1 Historical Realtime MiddleManager Druid Broker Druid Broker Broker Broker
v1 v2
API
groupBy v1 maxResults groupBy v2 groupBy v1 groupBy v2 v1 v2
groupBy v1 groupBy v2 1/4
groupBy v1 Broker Historical groupBy v2 Historical
groupBy v2
druid.processing.buffer.sizeBytes, , druid.processing.numMergeBuffers groupBy
druid.query.groupBy.maxMergingDictionarySize,
druid.query.groupBy.maxOnDiskStorage: 0
maxOnDiskStorage 0 Resource limit exceeded
maxOnDiskStorage 0 maxOnDiskStorage Resource limit exceeded
groupBy v2 druid.processing.numMergeBuffers ) Druid
Broker groupBy query subtotals groupBy
Historical groupBy
groupBy v1 druid.query.groupBy.maxResults Resource limit exceeded JVM
Druid groupBy limit Historical Broker orderBy orderBy limitPushDown , , topN , forceLimitPushDown
groupBy v2 bucket
bucket 1024 0.7 bufferGrouperInitialBuckets bufferGrouperMaxLoadFactor
Historical Broker N Historical druid.processing.numThreads ) http Broker
groupBy Druid GroupBy timeseries topN
groupBy groupBy numParallelCombineThreads
groupBy v2 intermediateCombineDegree
Historical groupBy v2
groupBy
Timeseries groupBy
TopN groupBy
GroupBy
groupby( query ) v1 v2 broker groupBy , v1 Druid v2 Broker
groupBy Broker Historical MiddleManager runtime.properties,
groupBy v2
druid.query.groupBy.numParallelCombineThreads
1 druid.query.groupBy.numParallelCombineThreads druid.processing.numThreads
applyLimitPushDownToSegment
Broker limit Historical Peon druid.query.groupBy.applyLimitPushDownToSegment
以上就是GroupBy · ApacheDruid中文技术文档（group by distribute by）的详细内容，想要了解更多 GroupBy · ApacheDruid中文技术文档的内容，请持续关注盛行IT软件开发工作室。
郑重声明：本文由网友发布，不代表盛行IT的观点，版权归原作者所有，仅为传播更多信息之目的，如有侵权请联系，我们将第一时间修改或删除，多谢。