Added support for custom update function to elasticizer

R/elastic_update.R

@@ -25,4 +25,4 @@ elastic_update <- function(x, es_super = 'secret') {
   # content(res, "parsed", "application/json")
   # appData <- content(res)
   return(res)
-}
+}

R/elasticizer.R

@@ -4,6 +4,7 @@
 #' @param query A JSON-formatted query in the Elasticsearch query DSL
 #' @param src Logical (true/false) indicating whether or not the source of each document should be retrieved
 #' @param index The name of the Elasticsearch index to search through
+#' @param update When set, indicates an update function to use on each batch of 1000 articles
 
 #' @return A data frame containing all the search results
 #' @export
@@ -12,7 +13,7 @@
 #################################################################################################
 #################################### Get data from ElasticSearch ################################
 #################################################################################################
-elasticizer <- function(query, src = T, index = 'maml', es_pwd = .rs.askForPassword("Elasticsearch READ")){
+elasticizer <- function(query, src = T, index = 'maml', es_pwd = .rs.askForPassword("Elasticsearch READ"), update = NULL){
   connect(es_port = 443,
           es_transport = 'https',
           es_host = 'linux01.uis.no',
@@ -21,7 +22,7 @@ elasticizer <- function(query, src = T, index = 'maml', es_pwd = .rs.askForPassw
           es_pwd = es_pwd,
           errors = 'complete')
   # Get all results - one approach is to use a while loop
-  if (src == T) {
+  if (src == T || length(update) > 0 ) {
     res <- Search(index = index, time_scroll="5m",body = query, size = 1000, raw=T)
   }
   if (src == F) {
@@ -36,6 +37,9 @@ elasticizer <- function(query, src = T, index = 'maml', es_pwd = .rs.askForPassw
     hits <- 1
     batch <- 1
     print(paste0('Processing documents ',batch*1000-1000,' through ',batch*1000,' out of ',total,' documents.'))
+    if (length(update) > 0){
+      update()
+    }
     while(hits != 0){
       res <- scroll(json$`_scroll_id`, time_scroll="5m", raw=T)
       json <- fromJSON(res)
@@ -43,9 +47,13 @@ elasticizer <- function(query, src = T, index = 'maml', es_pwd = .rs.askForPassw
       if(hits > 0) {
         batch <- batch+1
         print(paste0('Processing documents ',batch*1000-1000,' through ',batch*1000,' out of ',total,' documents.'))
-        out <- bind_rows(out, jsonlite:::flatten(json$hits$hits))
+        if (length(update) > 0){
+          update()
+        } else {
+          out <- bind_rows(out, jsonlite:::flatten(json$hits$hits))
+        }
       }
     }
     return(out)
   }
-}
+}

man/elasticizer.Rd

@@ -5,7 +5,7 @@
 \title{Generate a data frame out of unparsed Elasticsearch JSON}
 \usage{
 elasticizer(query, src = T, index = "maml",
-  es_pwd = .rs.askForPassword("Elasticsearch READ"))
+  es_pwd = .rs.askForPassword("Elasticsearch READ"), update = NULL)
 }
 \arguments{
 \item{query}{A JSON-formatted query in the Elasticsearch query DSL}
@@ -13,6 +13,8 @@ elasticizer(query, src = T, index = "maml",
 \item{src}{Logical (true/false) indicating whether or not the source of each document should be retrieved}
 
 \item{index}{The name of the Elasticsearch index to search through}
+
+\item{update}{When set, indicates an update function to use on each batch of 1000 articles}
 }
 \value{
 A data frame containing all the search results