aggregation

问题 Firstly i apologise if the terminology i use is incorrect as i am learning elasticsearch day by day and maybe use incorrect phrases. After spending several days trying to figure this out and pulling my hair out i seem to be hitting brick walls every-time. I am trying to get elasticsearch to provide a document count for each returned result, I will provide an example below.. { "suggest": { "text": "aberdeen", "city": { "completion": { "field": "city_suggest", "size": "2" } }, "street": {

问题 Consider I have an odata query like this: Sessions?$apply=filter(SomeColumn eq 1)/groupby((Application/Name), aggregate(TotalLaunchesCount with sum as Total)) Sessions and Application entities are linked by ApplicationId. I want to apply orderby on "Total" and get top 5 results as odata query response. I tried adding &$top=5 at the end of the above mentioned query. Its says: The query specified in the URI is not valid. Could not find a property named 'Total' on type 'Sessions'. Can anyone

问题 I want to run multiple facets in one aggregation to save db round trips. Here is my spring data code : final BalancesDTO total = this.mongoTemplate.aggregate( newAggregation( /* * Get all fund transactions for this user */ match(where("userId").is(userId)), /* * Summarize Confirmed Debits */ facet( match(where("entryType").is(EntryType.DEBIT) .andOperator(where("currentStatus").is(TransactionStatus.CONFIRMED))), unwind("history"), match(where("history.status").is(TransactionStatus.CONFIRMED))

问题 I'm trying to use ddply (a plyr function) to sort and identify the most frequent interaction type between any unique pairs of user from a social media data of the following form from <- c('A', 'A', 'A', 'B', 'B', 'B', 'B', 'C', 'C', 'C', 'C', 'D', 'D', 'D', 'D') to <- c('B', 'B', 'D', 'A', 'C', 'C', 'D', 'A', 'D', 'B', 'A', 'B', 'B', 'A', 'C') interaction_type <- c('like', 'comment', 'share', 'like', 'like', 'like', 'comment', 'like', 'like', 'share', 'like', 'comment', 'like', 'share', 'like

问题 I want to create an Aggregation that can be used in MongoOperations's aggregate() function. So for creating the Aggregation, I used a list of AggregationOperation as follows: ApplicationContext ctx = new AnnotationConfigApplicationContext(MongoConfig.class); MongoOperations mongoOperation = (MongoOperations) ctx.getBean("mongoTemplate"); List<AggregationOperation> aggregationOperations = new ArrayList<AggregationOperation>(); aggregationOperations.add(new MatchOperation(Criteria.where(

问题 I am completely new to gnuplot and am only trying this because I need to learn it. I have a values in three columns where the first represents the filename (date and time, one hour interval) and the remaining two columns represent two different entities Prop1 and Prop2. Datetime Prop1 Prop2 20110101_0000.txt 2 5 20110101_0100.txt 2 5 20110101_0200.txt 2 5 ... 20110101_2300.txt 2 5 20110201_0000.txt 2 5 20110101_0100.txt 2 5 ... 20110201_2300.txt 2 5 ... I need to aggregate the data by the

问题 For example, I have an object model: Product { int ProductId, string Name, List<Sale> Sales } I want to use the aggregate queries to get total Amount of Sales: GET: Product?$apply=groupby(Name, aggregate(Sales(Amount with sum as Total))) (follow as oasis-open standard) --> Got error: UriQueryExpressionParser_CloseParenOrCommaExpected=" ')' or ',' expected at position {0} in '{1}'. ". position at Amount. I change the query to: GET: Product?$apply=groupby(Name, aggregate(Sales/Amount with sum

问题 This question is an extension of a question I asked yesterday, but I will rephrase Using a data frame and pandas, I am trying to figure out what the tip percentage is for each category in a group by. So, using the tips database, I want to see, for each sex/smoker, what the tip percentage is is for female smoker / all female and for female non smoker / all female (and the same thing for men) When I do this, import pandas as pd df=pd.read_csv("https://raw.githubusercontent.com/wesm/pydata-book

问题 Suppose I have a Mongo DB with only one collection data . In this collection, I have the following documents: { "type": "person", "value": { "id": 1, "name": "Person 1", "age": 10 } }, { "type": "person", "value": { "id": 2, "name": "Person 2", "age": 20 } }, { "type": "prescription", "value": { "drug": "Bromhexine", "patient": 2 } }, { "type": "prescription", "value": { "drug": "Aspirin", "patient": 1 } } With those records, I'd like to make a JOIN between documents with "type": person and

问题 I'm trying to find a way to calculate the mean of rows in a Spark Dataframe in Scala where I want to ignore NAs. In R, there is a very convenient function called rowMeans where one can specify to ignore NAs: rowmeans(df,na.rm=TRUE) I'm unable to find a corresponding function for Spark Dataframes, and I wonder if anyone has a suggestion or input if this would be possible. Replacing them with 0 won't due since this will affect the denominator. I found a similar question here, however my