fix(jobs): update the API

#### jobs:v3p1beta1 The following keys were changed: - schemas.HistogramQuery.properties.histogramQuery.description - schemas.JobQuery.properties.companyDisplayNames.description - schemas.PostalAddress.properties.regionCode.description #### jobs:v3 The following keys were changed: - schemas.JobQuery.properties.companyDisplayNames.description - schemas.PostalAddress.properties.regionCode.description #### jobs:v4 The following keys were changed: - schemas.JobQuery.properties.companyDisplayNames.description - schemas.PostalAddress.properties.regionCode.description - schemas.SearchJobsRequest.properties.histogramQueries.description
googleapis · Mar 14, 2022 · 3820d87 · 3820d87
1 parent daa20c3
commit 3820d87
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Showing 6 changed files with 19 additions and 19 deletions.
diff --git a/discovery/jobs-v3.json b/discovery/jobs-v3.json
@@ -651,7 +651,7 @@
       }
     }
   },
-  "revision": "20210830",
+  "revision": "20220303",
   "rootUrl": "https://jobs.googleapis.com/",
   "schemas": {
     "ApplicationInfo": {
@@ -1901,7 +1901,7 @@
           "description": "Optional. Allows filtering jobs by commute time with different travel methods (for example, driving or public transit). Note: This only works with COMMUTE MODE. When specified, [JobQuery.location_filters] is ignored. Currently we don't support sorting by commute time."
         },
         "companyDisplayNames": {
-          "description": "Optional. This filter specifies the exact company display name of the jobs to search against. If a value isn't specified, jobs within the search results are associated with any company. If multiple values are specified, jobs within the search results may be associated with any of the specified companies. At most 20 company display name filters are allowed.",
+          "description": "Optional. This filter specifies the company Company.display_name of the jobs to search against. The company name must match the value exactly. Alternatively, if the value being searched for is wrapped in SUBSTRING_MATCH([value]), the company name must contain a case insensitive substring match of the value. Using this function may increase latency. Sample Value: SUBSTRING_MATCH(google) If a value isn't specified, jobs within the search results are associated with any company. If multiple values are specified, jobs within the search results may be associated with any of the specified companies. At most 20 company display name filters are allowed.",
           "items": {
             "type": "string"
           },
@@ -2453,7 +2453,7 @@
           "type": "array"
         },
         "regionCode": {
-          "description": "Required. CLDR region code of the country/region of the address. This is never inferred and it is up to the user to ensure the value is correct. See http://cldr.unicode.org/ and http://www.unicode.org/cldr/charts/30/supplemental/territory_information.html for details. Example: \"CH\" for Switzerland.",
+          "description": "Required. CLDR region code of the country/region of the address. This is never inferred and it is up to the user to ensure the value is correct. See https://cldr.unicode.org/ and https://www.unicode.org/cldr/charts/30/supplemental/territory_information.html for details. Example: \"CH\" for Switzerland.",
           "type": "string"
         },
         "revision": {

diff --git a/discovery/jobs-v3p1beta1.json b/discovery/jobs-v3p1beta1.json
@@ -681,7 +681,7 @@
       }
     }
   },
-  "revision": "20210830",
+  "revision": "20220303",
   "rootUrl": "https://jobs.googleapis.com/",
   "schemas": {
     "ApplicationInfo": {
@@ -1471,7 +1471,7 @@
       "id": "HistogramQuery",
       "properties": {
         "histogramQuery": {
-          "description": "An expression specifies a histogram request against matching resources (for example, jobs) for searches. Expression syntax is a aggregation function call with histogram facets and other options. Available aggregation function calls are: * `count(string_histogram_facet)`: Count the number of matching entity, for each distinct attribute value. * `count(numeric_histogram_facet, list of buckets)`: Count the number of matching entity within each bucket. Data types: * Histogram facet: facet names with format a-zA-Z+. * String: string like \"any string with backslash escape for quote(\\\").\" * Number: whole number and floating point number like 10, -1 and -0.01. * List: list of elements with comma(,) separator surrounded by square brackets. For example, [1, 2, 3] and [\"one\", \"two\", \"three\"]. Built-in constants: * MIN (minimum number similar to java Double.MIN_VALUE) * MAX (maximum number similar to java Double.MAX_VALUE) Built-in functions: * bucket(start, end[, label]): bucket built-in function creates a bucket with range of start, end). Note that the end is exclusive. For example, bucket(1, MAX, \"positive number\") or bucket(1, 10). Job histogram facets: * company_id: histogram by [Job.distributor_company_id. * company_display_name: histogram by Job.company_display_name. * employment_type: histogram by Job.employment_types. For example, \"FULL_TIME\", \"PART_TIME\". * company_size: histogram by CompanySize, for example, \"SMALL\", \"MEDIUM\", \"BIG\". * publish_time_in_day: histogram by the Job.publish_time in days. Must specify list of numeric buckets in spec. * publish_time_in_month: histogram by the Job.publish_time in months. Must specify list of numeric buckets in spec. * publish_time_in_year: histogram by the Job.publish_time in years. Must specify list of numeric buckets in spec. * degree_type: histogram by the Job.degree_type. For example, \"Bachelors\", \"Masters\". * job_level: histogram by the Job.job_level. For example, \"Entry Level\". * country: histogram by the country code of jobs. For example, \"US\", \"FR\". * admin1: histogram by the admin1 code of jobs, which is a global placeholder referring to the state, province, or the particular term a country uses to define the geographic structure below the country level. For example, \"CA\", \"IL\". * city: histogram by a combination of the \"city name, admin1 code\". For example, \"Mountain View, CA\", \"New York, NY\". * admin1_country: histogram by a combination of the \"admin1 code, country\". For example, \"CA, US\", \"IL, US\". * city_coordinate: histogram by the city center's GPS coordinates (latitude and longitude). For example, 37.4038522,-122.0987765. Since the coordinates of a city center can change, customers may need to refresh them periodically. * locale: histogram by the Job.language_code. For example, \"en-US\", \"fr-FR\". * language: histogram by the language subtag of the Job.language_code. For example, \"en\", \"fr\". * category: histogram by the JobCategory. For example, \"COMPUTER_AND_IT\", \"HEALTHCARE\". * base_compensation_unit: histogram by the CompensationUnit of base salary. For example, \"WEEKLY\", \"MONTHLY\". * base_compensation: histogram by the base salary. Must specify list of numeric buckets to group results by. * annualized_base_compensation: histogram by the base annualized salary. Must specify list of numeric buckets to group results by. * annualized_total_compensation: histogram by the total annualized salary. Must specify list of numeric buckets to group results by. * string_custom_attribute: histogram by string Job.custom_attributes. Values can be accessed via square bracket notations like string_custom_attribute[\"key1\"]. * numeric_custom_attribute: histogram by numeric Job.custom_attributes. Values can be accessed via square bracket notations like numeric_custom_attribute[\"key1\"]. Must specify list of numeric buckets to group results by. Example expressions: * count(admin1) * count(base_compensation, [bucket(1000, 10000), bucket(10000, 100000), bucket(100000, MAX)]) * count(string_custom_attribute[\"some-string-custom-attribute\"]) * count(numeric_custom_attribute[\"some-numeric-custom-attribute\"], [bucket(MIN, 0, \"negative\"), bucket(0, MAX, \"non-negative\")])",
+          "description": "An expression specifies a histogram request against matching resources (for example, jobs) for searches. Expression syntax is a aggregation function call with histogram facets and other options. Available aggregation function calls are: * `count(string_histogram_facet)`: Count the number of matching entity, for each distinct attribute value. * `count(numeric_histogram_facet, list of buckets)`: Count the number of matching entity within each bucket. A maximum of 200 histogram buckets are supported. Data types: * Histogram facet: facet names with format a-zA-Z+. * String: string like \"any string with backslash escape for quote(\\\").\" * Number: whole number and floating point number like 10, -1 and -0.01. * List: list of elements with comma(,) separator surrounded by square brackets. For example, [1, 2, 3] and [\"one\", \"two\", \"three\"]. Built-in constants: * MIN (minimum number similar to java Double.MIN_VALUE) * MAX (maximum number similar to java Double.MAX_VALUE) Built-in functions: * bucket(start, end[, label]): bucket built-in function creates a bucket with range of start, end). Note that the end is exclusive. For example, bucket(1, MAX, \"positive number\") or bucket(1, 10). Job histogram facets: * company_id: histogram by [Job.distributor_company_id. * company_display_name: histogram by Job.company_display_name. * employment_type: histogram by Job.employment_types. For example, \"FULL_TIME\", \"PART_TIME\". * company_size: histogram by CompanySize, for example, \"SMALL\", \"MEDIUM\", \"BIG\". * publish_time_in_day: histogram by the Job.publish_time in days. Must specify list of numeric buckets in spec. * publish_time_in_month: histogram by the Job.publish_time in months. Must specify list of numeric buckets in spec. * publish_time_in_year: histogram by the Job.publish_time in years. Must specify list of numeric buckets in spec. * degree_type: histogram by the Job.degree_type. For example, \"Bachelors\", \"Masters\". * job_level: histogram by the Job.job_level. For example, \"Entry Level\". * country: histogram by the country code of jobs. For example, \"US\", \"FR\". * admin1: histogram by the admin1 code of jobs, which is a global placeholder referring to the state, province, or the particular term a country uses to define the geographic structure below the country level. For example, \"CA\", \"IL\". * city: histogram by a combination of the \"city name, admin1 code\". For example, \"Mountain View, CA\", \"New York, NY\". * admin1_country: histogram by a combination of the \"admin1 code, country\". For example, \"CA, US\", \"IL, US\". * city_coordinate: histogram by the city center's GPS coordinates (latitude and longitude). For example, 37.4038522,-122.0987765. Since the coordinates of a city center can change, customers may need to refresh them periodically. * locale: histogram by the Job.language_code. For example, \"en-US\", \"fr-FR\". * language: histogram by the language subtag of the Job.language_code. For example, \"en\", \"fr\". * category: histogram by the JobCategory. For example, \"COMPUTER_AND_IT\", \"HEALTHCARE\". * base_compensation_unit: histogram by the CompensationUnit of base salary. For example, \"WEEKLY\", \"MONTHLY\". * base_compensation: histogram by the base salary. Must specify list of numeric buckets to group results by. * annualized_base_compensation: histogram by the base annualized salary. Must specify list of numeric buckets to group results by. * annualized_total_compensation: histogram by the total annualized salary. Must specify list of numeric buckets to group results by. * string_custom_attribute: histogram by string Job.custom_attributes. Values can be accessed via square bracket notations like string_custom_attribute[\"key1\"]. * numeric_custom_attribute: histogram by numeric Job.custom_attributes. Values can be accessed via square bracket notations like numeric_custom_attribute[\"key1\"]. Must specify list of numeric buckets to group results by. Example expressions: * count(admin1) * count(base_compensation, [bucket(1000, 10000), bucket(10000, 100000), bucket(100000, MAX)]) * count(string_custom_attribute[\"some-string-custom-attribute\"]) * count(numeric_custom_attribute[\"some-numeric-custom-attribute\"], [bucket(MIN, 0, \"negative\"), bucket(0, MAX, \"non-negative\")])",
           "type": "string"
         }
       },
@@ -1998,7 +1998,7 @@
           "description": "Optional. Allows filtering jobs by commute time with different travel methods (for example, driving or public transit). Note: This only works with COMMUTE MODE. When specified, [JobQuery.location_filters] is ignored. Currently we don't support sorting by commute time."
         },
         "companyDisplayNames": {
-          "description": "Optional. This filter specifies the exact company display name of the jobs to search against. If a value isn't specified, jobs within the search results are associated with any company. If multiple values are specified, jobs within the search results may be associated with any of the specified companies. At most 20 company display name filters are allowed.",
+          "description": "Optional. This filter specifies the company Company.display_name of the jobs to search against. The company name must match the value exactly. Alternatively, if the value being searched for is wrapped in SUBSTRING_MATCH([value]), the company name must contain a case insensitive substring match of the value. Using this function may increase latency. Sample Value: SUBSTRING_MATCH(google) If a value isn't specified, jobs within the search results are associated with any company. If multiple values are specified, jobs within the search results may be associated with any of the specified companies. At most 20 company display name filters are allowed.",
           "items": {
             "type": "string"
           },
@@ -2592,7 +2592,7 @@
           "type": "array"
         },
         "regionCode": {
-          "description": "Required. CLDR region code of the country/region of the address. This is never inferred and it is up to the user to ensure the value is correct. See http://cldr.unicode.org/ and http://www.unicode.org/cldr/charts/30/supplemental/territory_information.html for details. Example: \"CH\" for Switzerland.",
+          "description": "Required. CLDR region code of the country/region of the address. This is never inferred and it is up to the user to ensure the value is correct. See https://cldr.unicode.org/ and https://www.unicode.org/cldr/charts/30/supplemental/territory_information.html for details. Example: \"CH\" for Switzerland.",
           "type": "string"
         },
         "revision": {