Search Knowledge Graphs

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/**
* Initialization function that connects to a knowledge graph and displays the data model and service definition.
* The data model is used to populate the dropdowns in the search with the correct named types and IDs.
*/
require([
  "esri/rest/knowledgeGraphService",
], (KGModule ) => {
  //url to the knowledge graph server
  const url = "https://sampleserver7.arcgisonline.com/server/rest/services/Hosted/BumbleBees/KnowledgeGraphServer"
  const init = async () => {
    //get the knowledge graph data model and service definition.
    knowledgeGraph = await KGModule.fetchKnowledgeGraph(url);

    //display the data model and service definition for the knowledge graph
    dataDiv.innerHTML = `<h3>Knowledge Graph</h3><calcite-tree>${buildList(knowledgeGraph, false,true)}</calcite-tree>`;
  }
  init()
...
)

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/**
* Basic search to return any information related to the search term.
* Search is limited by the maxRecordCount parameter in the serviceDefinition of the graph.
*/
document
  .getElementById('search-button').addEventListener('click', async (e) => {
    const searchString = document.getElementById("search-keyword").value
    const typeFilter = document.getElementById("search-type-filter").value
    // execute search
    const searchResults = await KGModule.executeSearch(knowledgeGraph, {
      searchQuery: searchString,
      typeCategoryFilter: typeFilter
    })
    // display results
    const html = buildList(searchResults.resultRows, false, true)
    dataDiv.innerHTML = `<h3>Search Results</h3><calcite-tree>${html}</calcite-tree>`;
  })

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/**
* Streaming search to return the specified number of entities or relationships (or both)
* that contain the search term starting at the specified index.
* It will only search the named types specified or the ids specified.
* If neither are specified, it will search the entire graph.
* Streaming search has more options to refine the search results.
* Streaming search also has much higher performance when working with large datasets.
* It returns the data in chunks that can be processed as they are returned.
*/
document
  .getElementById('streaming-search-button').addEventListener('click', async (e) => {
    dataDiv.innerHTML = '';
    const searchString = document.getElementById("streaming-search-keyword").value
    const typeFilter = document.getElementById("streaming-search-type-filter").value
    const namedTypes = document.getElementById("streaming-search-named-types").value
    const index = document.getElementById("streaming-search-start-index").value
    const limit = document.getElementById("streaming-search-limit").value
    const ids = document.getElementById("streaming-search-ids").value
    const context = document.getElementById('streaming-search-context').checked
    //construct the search object
    const searchParams = {
      searchQuery: searchString,
      typeCategoryFilter: typeFilter,
      returnSearchContext: context,
    }
    if (index) { searchParams["start"] = index };
    if (limit) { searchParams["num"] = limit };
    if (namedTypes) { searchParams["namedTypesFilter"] = namedTypes };
    if (ids) { searchParams["idsFilter"] = ids };
    //execute the search and read the result
    const searchResults = await KGModule.executeSearchStreaming(knowledgeGraph, searchParams)
    readStream(searchResults);
  })

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// a function to read the stream returned from the streaming search
const readStream = async (streamingQueryResult, method) => {
  //create the reader
  let reader = streamingQueryResult.resultRowsStream.getReader();
  //try to read the stream
  try {
    while (true) {
      //read the stream
      const { done, value } = await reader.read();
      //create the output list from the read stream.
      dataDiv.innerHTML += `<h3>Search Results</h3><calcite-tree>${buildList(value, false, true)}</calcite-tree>`
      //stop reader when the stream is done
      if (done) {
        break;
      }
    }
  // if there is an error in returning the stream or the stream is aborted
  } catch (err) {
    if (err.name === "AbortError") {
      console.log("Request aborted as expected");
    } else {
      throw err;
    }
  }
};