直方图

Cloud Talent Solution 可通过直方图的形式向您显示与给定搜索关联的职位数量。直方图搜索会返回与特定查询匹配的所有职位的计数,并按请求的 SearchMode 细分。例如,直方图搜索可能会按照工作性质(全职、兼职等)返回加州山景城已有的职位数量。

直方图通常与搜索调用并行运行,并使用相同的 JobQueryrequestMetadata

直方图由 histogramQuery 字段定义,该字段是单个字符串表达式。如需详细了解适用于直方图查询的功能,请参阅 histogramQuery 文档

检索直方图

以下代码示例会返回直方图结果:

Go

import (
	"context"
	"fmt"
	"io"

	talent "cloud.google.com/go/talent/apiv4beta1"
	"google.golang.org/api/iterator"
	talentpb "google.golang.org/genproto/googleapis/cloud/talent/v4beta1"
)

// histogramSearch searches for jobs with histogram queries.
func histogramSearch(w io.Writer, projectID, companyID string) error {
	ctx := context.Background()

	// Initialize a jobService client.
	c, err := talent.NewJobClient(ctx)
	if err != nil {
		fmt.Printf("talent.NewJobClient: %v\n", err)
		return err
	}

	// Construct a searchJobs request.
	req := &talentpb.SearchJobsRequest{
		Parent: fmt.Sprintf("projects/%s", projectID),
		// Make sure to set the RequestMetadata the same as the associated
		// search request.
		RequestMetadata: &talentpb.RequestMetadata{
			// Make sure to hash your userId.
			UserId: "HashedUsrID",
			// Make sure to hash the sessionId.
			SessionId: "HashedSessionID",
			// Domain of the website where the search is conducted.
			Domain: "www.googlesample.com",
		},
		HistogramQueries: []*talentpb.HistogramQuery{
			{
				// More info on histogram facets, constants, and built-in functions:
				// https://godoc.org/google.golang.org/genproto/googleapis/cloud/talent/v4beta1#SearchJobsRequest
				HistogramQuery: "count(base_compensation, [bucket(12, 20)])",
			},
		},
	}
	if companyID != "" {
		req.JobQuery = &talentpb.JobQuery{
			CompanyNames: []string{fmt.Sprintf("projects/%s/companies/%s", projectID, companyID)},
		}
	}

	it := c.SearchJobs(ctx, req)

	for {
		resp, err := it.Next()
		if err == iterator.Done {
			return nil
		}
		if err != nil {
			fmt.Printf("it.Next: %v\n", err)
			return err
		}
		fmt.Fprintf(w, "Job: %q\n", resp.Job.GetName())
	}
}

Java

如需详细了解如何安装和创建 Cloud Talent Solution 客户端,请参阅 Cloud Talent Solution 客户端库


import com.google.cloud.talent.v4.HistogramQuery;
import com.google.cloud.talent.v4.Job;
import com.google.cloud.talent.v4.JobServiceClient;
import com.google.cloud.talent.v4.RequestMetadata;
import com.google.cloud.talent.v4.SearchJobsRequest;
import com.google.cloud.talent.v4.SearchJobsResponse;
import com.google.cloud.talent.v4.TenantName;
import java.io.IOException;

public class HistogramSearchJobs {

  public static void searchJobs() throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String tenantId = "your-tenant-id";
    String query = "count(base_compensation, [bucket(12, 20)])";
    searchJobs(projectId, tenantId, query);
  }

  // Search Jobs with histogram queries.
  public static void searchJobs(String projectId, String tenantId, String query)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (JobServiceClient jobServiceClient = JobServiceClient.create()) {
      TenantName parent = TenantName.of(projectId, tenantId);

      String domain = "http://www.jobUrl.com";
      String sessionId = "Hashed session identifier";
      String userId = "Hashed user identifier";
      RequestMetadata requestMetadata =
          RequestMetadata.newBuilder()
              .setDomain(domain)
              .setSessionId(sessionId)
              .setUserId(userId)
              .build();
      HistogramQuery histogramQueriesElement =
          HistogramQuery.newBuilder().setHistogramQuery(query).build();
      SearchJobsRequest request =
          SearchJobsRequest.newBuilder()
              .setParent(parent.toString())
              .setRequestMetadata(requestMetadata)
              .addHistogramQueries(histogramQueriesElement)
              .build();

      for (SearchJobsResponse.MatchingJob responseItem :
          jobServiceClient.searchJobs(request).getMatchingJobsList()) {
        System.out.format("Job summary: %s%n", responseItem.getJobSummary());
        System.out.format("Job title snippet: %s%n", responseItem.getJobTitleSnippet());
        Job job = responseItem.getJob();
        System.out.format("Job name: %s%n", job.getName());
        System.out.format("Job title: %s%n", job.getTitle());
      }
    }
  }
}

Node.js

如需详细了解如何安装和创建 Cloud Talent Solution 客户端,请参阅 Cloud Talent Solution 客户端库


const talent = require('@google-cloud/talent').v4;

/**
 * Search Jobs with histogram queries
 *
 * @param query {string} Histogram query
 * More info on histogram facets, constants, and built-in functions:
 * https://godoc.org/google.golang.org/genproto/googleapis/cloud/talent/v4beta1#SearchJobsRequest
 */
function sampleSearchJobs(projectId, tenantId, query) {
  const client = new talent.JobServiceClient();
  // Iterate over all elements.
  // const projectId = 'Your Google Cloud Project ID';
  // const tenantId = 'Your Tenant ID (using tenancy is optional)';
  // const query = 'count(base_compensation, [bucket(12, 20)])';
  const formattedParent = client.tenantPath(projectId, tenantId);
  const domain = 'www.example.com';
  const sessionId = 'Hashed session identifier';
  const userId = 'Hashed user identifier';
  const requestMetadata = {
    domain: domain,
    sessionId: sessionId,
    userId: userId,
  };
  const histogramQueriesElement = {
    histogramQuery: query,
  };
  const histogramQueries = [histogramQueriesElement];
  const request = {
    parent: formattedParent,
    requestMetadata: requestMetadata,
    histogramQueries: histogramQueries,
  };

  client
    .searchJobs(request)
    .then(responses => {
      const resources = responses[0];
      for (const resource of resources.matchingJobs) {
        console.log(`Job summary: ${resource.jobSummary}`);
        console.log(`Job title snippet: ${resource.jobTitleSnippet}`);
        const job = resource.job;
        console.log(`Job name: ${job.name}`);
        console.log(`Job title: ${job.title}`);
      }
    })
    .catch(err => {
      console.error(err);
    });
}

Python

如需详细了解如何安装和创建 Cloud Talent Solution 客户端,请参阅 Cloud Talent Solution 客户端库


from google.cloud import talent
import six

def search_jobs(project_id, tenant_id, query):
    """
    Search Jobs with histogram queries

    Args:
      query Histogram query
      More info on histogram facets, constants, and built-in functions:
      https://godoc.org/google.golang.org/genproto/googleapis/cloud/talent/v4beta1#SearchJobsRequest
    """

    client = talent.JobServiceClient()

    # project_id = 'Your Google Cloud Project ID'
    # tenant_id = 'Your Tenant ID (using tenancy is optional)'
    # query = 'count(base_compensation, [bucket(12, 20)])'

    if isinstance(project_id, six.binary_type):
        project_id = project_id.decode("utf-8")
    if isinstance(tenant_id, six.binary_type):
        tenant_id = tenant_id.decode("utf-8")
    if isinstance(query, six.binary_type):
        query = query.decode("utf-8")
    parent = f"projects/{project_id}/tenants/{tenant_id}"
    domain = "www.example.com"
    session_id = "Hashed session identifier"
    user_id = "Hashed user identifier"
    request_metadata = {"domain": domain, "session_id": session_id, "user_id": user_id}
    histogram_queries_element = {"histogram_query": query}
    histogram_queries = [histogram_queries_element]

    # Iterate over all results
    results = []
    request = talent.SearchJobsRequest(
        parent=parent,
        request_metadata=request_metadata,
        histogram_queries=histogram_queries,
    )
    for response_item in client.search_jobs(request=request).matching_jobs:
        print("Job summary: {response_item.job_summary}")
        print("Job title snippet: {response_item.job_title_snippet}")
        job = response_item.job
        results.append(job)
        print("Job name: {job.name}")
        print("Job title: {job.title}")
    return results

相关性阈值

直方图请求不使用相关性阈值。要确保直方图搜索与相同的职位搜索之间的计数一致,职位搜索中的 disableKeywordMatch 必须为 false