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62 lines
3.0 KiB
62 lines
3.0 KiB
### Notes:
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# Do you want to search for either one OR other actorid, or both occuring in the same document?
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# Do you want to keep only the occurences of the actorids you are searching for, or all actor occurences in the hits?
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# Search by actorId, then aggregate by month
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# When actorId starts with P_, define what hits you want to get (short, full, actor), if more than one, aggregate properly
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# Develop query generator for specific actors (ie combine actorId with start and end dates)
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#' Generate and store aggregate actor measures to elasticsearch
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#'
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#' Generate and store aggregate actor measures to elasticsearch
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#' @param out The output provided by elasticizer()
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#' @param localhost Boolean indicating if the script should run locally, or remote
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#' @param es_super Write password for ES
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#' @param actorids List of actorids used in the search, should be the same as the actorids used for elasticizer()
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#' @param ver String indicating the version of the update
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#' @return Return value is based on output of elastic_update()
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#' @export
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#' @examples
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#' aggregator_elastic(out, localhost = F, actorids, ver, es_super)
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#################################################################################################
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#################################### Aggregate actor results ################################
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#################################################################################################
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aggregator_elastic <- function(out, localhost = F, actorids, ver, es_super) {
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### Generating actor dataframe, unnest by actorsDetail, then by actor ids. Filter out non-relevant actor ids.
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partyid <- str_sub(actorids[1], end=-3)
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actor_df <- out %>%
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unnest() %>%
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unnest(ids, .preserve = colnames(.)) %>%
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filter(ids1 %in% actorids)
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agg_party_actors <- bind_rows(lapply(unique(actor_df$`_id`),
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mamlr:::aggregator,
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actor_df = actor_df,
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merge_id = paste0(partyid,'_mfsa')))
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party <- actor_df %>%
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filter(!endsWith(ids1, '_a'))
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agg_party <- bind_rows(lapply(unique(party$`_id`),
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mamlr:::aggregator,
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actor_df = party,
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merge_id = paste0(partyid,'_mfs')))
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actors_only <- actor_df %>%
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filter(endsWith(ids1, '_a'))
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agg_actors <- bind_rows(lapply(unique(actors_only$`_id`),
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mamlr:::aggregator,
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actor_df = actors_only,
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merge_id = paste0(partyid,'_ma')))
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df_out <- bind_rows(agg_party_actors, agg_party, agg_actors)
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doc_ids <- df_out$doc_id
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df_out <- df_out %>%
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select(-1) %>%
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split(as.factor(doc_ids))
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df_out <- data.frame(doc_id = names(df_out), list = I(df_out))
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bulk <- apply(df_out, 1, bulk_writer, varname ='actorsDetail', type = 'add', ver = ver)
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return(elastic_update(bulk, es_super = es_super, localhost = localhost))
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}
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