3 min read

Building a search page over large documente dataset based in elasticsearch

During these weeks of lockdown everyone in data science has been looking for some dataset to play around. In my particular case I found ParlSpeech V2 1. ParlSpeech V2 contains complete full-text vectors of more than 6.3 million parliamentary speeches in the key legislative chambers of Austria, the Czech Republic, Germany, Denmark, the Netherlands, New Zealand, Spain, Sweden, and the United Kingdom, covering periods between 21 and 32 years. Meta-data include information on date, speaker, party, and partially agenda item under which a speech was held. The accompanying release note provides a more detailed guide to the data.

This dataset reminded me of VERBA VOLANT from Civio, in this beatufil data visualization you can search words in the a dataset containing the news broadcasted in TVE, the spanish public television.

Then I thought about doing something similar and in their public repository I found out that they used Elastic, Elastic is an open source engine for documental texts. Elastic offers their own cloud service (free during the first 14 days). So I decided to get my hands dirty with Elastic and R.

Once I set up my own Elastic Cloud account, I populated it using elastic package in R

discursos <- readRDS("Corp_Congreso_V2.rds")
x <- connect(host = "4fa108dc0e82435d94e6b71b7723d0be.uksouth.azure.elastic-cloud.com",port = 9243,user = "elastic",pwd = "*****************",transport_schema = "https")
docs_bulk(x,discursos,index = "speechnumber")

And build a very simple shiny application with elastic capacities (so simple that it´s basically stripped off)


host <- "4fa108dc0e82435d94e6b71b7723d0be.uksouth.azure.elastic-cloud.com"
port <- 9243
usuario <- "elastic"
password <- "**************************"
x <- connect(host = host,port = port,user = usuario,pwd = password,transport_schema = "https")

# Define UI for application that draws a histogram

    # Application title
    titlePanel("Buscador de términos en discursos del Congreso de los Diputados usando elastic"),

    # Sidebar with a slider input for number of bins
    textInput("termino", "Buscar", value = ""),



# Define server logic required to draw a histogram
shinyServer(function(input, output) {
    output$table <- renderDataTable({
        # if(input$termino!=""){
            res <- elastic::Search(conn = x,index = "speechnumber",q = sprintf("text:%s",input$termino),source=c("speaker","date","text"),asdf = TRUE,size = 10000)
        # } else {
            #res <- elastic::Search(conn = x,index = "speechnumber",q = "text:*",source=c("speaker","date","text"),asdf = TRUE)
        # }
        df <- res$hits$hits
        df <- df %>% dplyr::select(starts_with("_source"))
        colnames(df) <- gsub(pattern = "_source.",replacement = "",x = colnames(df))

I’ve deployed my (very simple) application to shinyapps, you can find it here. I think Elastic and Kibana are amazing tools and I’ve enjoyed the time I’ve spent learning a little bit of them.

  1. Rauh, Christian; Schwalbach, Jan, 2020, “The ParlSpeech V2 data set: Full-text corpora of 6.3 million parliamentary speeches in the key legislative chambers of nine representative democracies”, https://doi.org/10.7910/DVN/L4OAKN, Harvard Dataverse, V1