| OLD | NEW |
| 1 { | 1 { |
| 2 "auth": { | 2 "auth": { |
| 3 "oauth2": { | 3 "oauth2": { |
| 4 "scopes": { | 4 "scopes": { |
| 5 "https://www.googleapis.com/auth/analytics.readonly": { | 5 "https://www.googleapis.com/auth/analytics.readonly": { |
| 6 "description": "View your Google Analytics data" | 6 "description": "View your Google Analytics data" |
| 7 }, | 7 }, |
| 8 "https://www.googleapis.com/auth/analytics": { | 8 "https://www.googleapis.com/auth/analytics": { |
| 9 "description": "View and manage your Google Analytics data" | 9 "description": "View and manage your Google Analytics data" |
| 10 } | 10 } |
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| 133 "$ref": "GetReportsResponse" | 133 "$ref": "GetReportsResponse" |
| 134 }, | 134 }, |
| 135 "scopes": [ | 135 "scopes": [ |
| 136 "https://www.googleapis.com/auth/analytics", | 136 "https://www.googleapis.com/auth/analytics", |
| 137 "https://www.googleapis.com/auth/analytics.readonly" | 137 "https://www.googleapis.com/auth/analytics.readonly" |
| 138 ] | 138 ] |
| 139 } | 139 } |
| 140 } | 140 } |
| 141 } | 141 } |
| 142 }, | 142 }, |
| 143 "revision": "20160616", | 143 "revision": "20160714", |
| 144 "rootUrl": "https://analyticsreporting.googleapis.com/", | 144 "rootUrl": "https://analyticsreporting.googleapis.com/", |
| 145 "schemas": { | 145 "schemas": { |
| 146 "PivotHeader": { | 146 "PivotHeader": { |
| 147 "description": "The headers for each of the pivot sections defined i
n the request.", | 147 "description": "The headers for each of the pivot sections defined i
n the request.", |
| 148 "id": "PivotHeader", | 148 "id": "PivotHeader", |
| 149 "properties": { | 149 "properties": { |
| 150 "totalPivotGroupsCount": { | 150 "totalPivotGroupsCount": { |
| 151 "description": "The total number of groups for this pivot.", | 151 "description": "The total number of groups for this pivot.", |
| 152 "format": "int32", | 152 "format": "int32", |
| 153 "type": "integer" | 153 "type": "integer" |
| 154 }, | 154 }, |
| 155 "pivotHeaderEntries": { | 155 "pivotHeaderEntries": { |
| 156 "description": "A single pivot section header.", | 156 "description": "A single pivot section header.", |
| 157 "items": { | 157 "items": { |
| 158 "$ref": "PivotHeaderEntry" | 158 "$ref": "PivotHeaderEntry" |
| 159 }, | 159 }, |
| 160 "type": "array" | 160 "type": "array" |
| 161 } | 161 } |
| 162 }, | 162 }, |
| 163 "type": "object" | 163 "type": "object" |
| 164 }, | 164 }, |
| 165 "Metric": { | 165 "Metric": { |
| 166 "description": "A metric in the request.", | 166 "description": "[Metrics](https://support.google.com/analytics/answe
r/1033861)\nare the quantitative measurements. For example, the metric `ga:users
`\nindicates the total number of users for the requested time period.", |
| 167 "id": "Metric", | 167 "id": "Metric", |
| 168 "properties": { | 168 "properties": { |
| 169 "alias": { | 169 "alias": { |
| 170 "description": "An alias for the metric expression is an alt
ernate name for the\nexpression. The alias can be used for filtering and sorting
. This field\nis optional and is useful if the expression is not a single metric
but\na complex expression which cannot be used in filtering and sorting.\nThe a
lias is also used in the response column header.", | 170 "description": "An alias for the metric expression is an alt
ernate name for the\nexpression. The alias can be used for filtering and sorting
. This field\nis optional and is useful if the expression is not a single metric
but\na complex expression which cannot be used in filtering and sorting.\nThe a
lias is also used in the response column header.", |
| 171 "type": "string" | 171 "type": "string" |
| 172 }, | 172 }, |
| 173 "formattingType": { | 173 "formattingType": { |
| 174 "description": "Specifies how the metric expression should b
e formatted, for example\n`INTEGER`.", | 174 "description": "Specifies how the metric expression should b
e formatted, for example\n`INTEGER`.", |
| 175 "enum": [ | 175 "enum": [ |
| 176 "METRIC_TYPE_UNSPECIFIED", | 176 "METRIC_TYPE_UNSPECIFIED", |
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| 407 }, | 407 }, |
| 408 "ReportRequest": { | 408 "ReportRequest": { |
| 409 "description": "The main request class which specifies the Reporting
API request.", | 409 "description": "The main request class which specifies the Reporting
API request.", |
| 410 "id": "ReportRequest", | 410 "id": "ReportRequest", |
| 411 "properties": { | 411 "properties": { |
| 412 "cohortGroup": { | 412 "cohortGroup": { |
| 413 "$ref": "CohortGroup", | 413 "$ref": "CohortGroup", |
| 414 "description": "Cohort group associated with this request. I
f there is a cohort group\nin the request the `ga:cohort` dimension must be pres
ent.\nEvery [ReportRequest](#ReportRequest) within a `batchGet` method must\ncon
tain the same `cohortGroup` definition." | 414 "description": "Cohort group associated with this request. I
f there is a cohort group\nin the request the `ga:cohort` dimension must be pres
ent.\nEvery [ReportRequest](#ReportRequest) within a `batchGet` method must\ncon
tain the same `cohortGroup` definition." |
| 415 }, | 415 }, |
| 416 "dimensions": { | 416 "dimensions": { |
| 417 "description": "Dimensions requested in the request.", | 417 "description": "The dimensions requested.\nRequests can have
a total of 7 dimensions.", |
| 418 "items": { | 418 "items": { |
| 419 "$ref": "Dimension" | 419 "$ref": "Dimension" |
| 420 }, | 420 }, |
| 421 "type": "array" | 421 "type": "array" |
| 422 }, | 422 }, |
| 423 "metricFilterClauses": { | 423 "metricFilterClauses": { |
| 424 "description": "The metric filter clauses. They are logicall
y combined with the `AND`\noperator. Metric filters look at only the first date
range and not the\ncomparing date range. Note that filtering on metrics occurs
after the\nmetrics are aggregated.", | 424 "description": "The metric filter clauses. They are logicall
y combined with the `AND`\noperator. Metric filters look at only the first date
range and not the\ncomparing date range. Note that filtering on metrics occurs
after the\nmetrics are aggregated.", |
| 425 "items": { | 425 "items": { |
| 426 "$ref": "MetricFilterClause" | 426 "$ref": "MetricFilterClause" |
| 427 }, | 427 }, |
| 428 "type": "array" | 428 "type": "array" |
| 429 }, | 429 }, |
| 430 "hideTotals": { | 430 "hideTotals": { |
| 431 "description": "If set to true, hides the total of all metri
cs for all the matching rows,\nfor every date range. The default false and will
return the totals.", | 431 "description": "If set to true, hides the total of all metri
cs for all the matching rows,\nfor every date range. The default false and will
return the totals.", |
| 432 "type": "boolean" | 432 "type": "boolean" |
| 433 }, | 433 }, |
| 434 "includeEmptyRows": { | 434 "includeEmptyRows": { |
| 435 "description": "If set to false, the response does not inclu
de rows if all the retrieved\nmetrics are equal to zero. The default is false wh
ich will exclude these\nrows.", | 435 "description": "If set to false, the response does not inclu
de rows if all the retrieved\nmetrics are equal to zero. The default is false wh
ich will exclude these\nrows.", |
| 436 "type": "boolean" | 436 "type": "boolean" |
| 437 }, | 437 }, |
| 438 "dimensionFilterClauses": { | 438 "dimensionFilterClauses": { |
| 439 "description": "The dimension filter clauses for filtering D
imension Values. They are\nlogically combined with the `AND` operator. Note that
filtering occurs\nbefore any dimensions are aggregated, so that the returned me
trics\nrepresent the total for only the relevant dimensions.", | 439 "description": "The dimension filter clauses for filtering D
imension Values. They are\nlogically combined with the `AND` operator. Note that
filtering occurs\nbefore any dimensions are aggregated, so that the returned me
trics\nrepresent the total for only the relevant dimensions.", |
| 440 "items": { | 440 "items": { |
| 441 "$ref": "DimensionFilterClause" | 441 "$ref": "DimensionFilterClause" |
| 442 }, | 442 }, |
| 443 "type": "array" | 443 "type": "array" |
| 444 }, | 444 }, |
| 445 "pivots": { | 445 "pivots": { |
| 446 "description": "The pivot definitions.", | 446 "description": "The pivot definitions. Requests can have a m
aximum of 2 pivots.", |
| 447 "items": { | 447 "items": { |
| 448 "$ref": "Pivot" | 448 "$ref": "Pivot" |
| 449 }, | 449 }, |
| 450 "type": "array" | 450 "type": "array" |
| 451 }, | 451 }, |
| 452 "dateRanges": { | 452 "dateRanges": { |
| 453 "description": "Date ranges in the request. The request can
have a maximum of 2 date\nranges. The response will contain a set of metric valu
es for each\ncombination of the dimensions for each date range in the request. S
o, if\nthere are two date ranges, there will be two set of metric values, one fo
r\nthe original date range and one for the second date range.\nThe `reportReques
t.dateRanges` field should not be specified for cohorts\nor Lifetime value reque
sts.\nIf a date range is not provided, the default date range is (startDate:\ncu
rrent date - 7 days, endDate: current date - 1 day). Every\n[ReportRequest](#Rep
ortRequest) within a `batchGet` method must\ncontain the same `dateRanges` defin
ition.", | 453 "description": "Date ranges in the request. The request can
have a maximum of 2 date\nranges. The response will contain a set of metric valu
es for each\ncombination of the dimensions for each date range in the request. S
o, if\nthere are two date ranges, there will be two set of metric values, one fo
r\nthe original date range and one for the second date range.\nThe `reportReques
t.dateRanges` field should not be specified for cohorts\nor Lifetime value reque
sts.\nIf a date range is not provided, the default date range is (startDate:\ncu
rrent date - 7 days, endDate: current date - 1 day). Every\n[ReportRequest](#Rep
ortRequest) within a `batchGet` method must\ncontain the same `dateRanges` defin
ition.", |
| 454 "items": { | 454 "items": { |
| 455 "$ref": "DateRange" | 455 "$ref": "DateRange" |
| 456 }, | 456 }, |
| (...skipping 16 matching lines...) Expand all Loading... |
| 473 ], | 473 ], |
| 474 "enumDescriptions": [ | 474 "enumDescriptions": [ |
| 475 "If the `samplingLevel` field is unspecified the `DEFAUL
T` sampling level\nis used.", | 475 "If the `samplingLevel` field is unspecified the `DEFAUL
T` sampling level\nis used.", |
| 476 "Returns response with a sample size that balances speed
and\naccuracy.", | 476 "Returns response with a sample size that balances speed
and\naccuracy.", |
| 477 "It returns a fast response with a smaller sampling size
.", | 477 "It returns a fast response with a smaller sampling size
.", |
| 478 "Returns a more accurate response using a large sampling
size. But this\nmay result in response being slower." | 478 "Returns a more accurate response using a large sampling
size. But this\nmay result in response being slower." |
| 479 ], | 479 ], |
| 480 "type": "string" | 480 "type": "string" |
| 481 }, | 481 }, |
| 482 "metrics": { | 482 "metrics": { |
| 483 "description": "Metrics, the quantitative measurements, requ
ested in the request.\nRequests must specify at least one metric.", | 483 "description": "The metrics requested.\nRequests must specif
y at least one metric. Requests can have a\ntotal of 10 metrics.", |
| 484 "items": { | 484 "items": { |
| 485 "$ref": "Metric" | 485 "$ref": "Metric" |
| 486 }, | 486 }, |
| 487 "type": "array" | 487 "type": "array" |
| 488 }, | 488 }, |
| 489 "pageSize": { | 489 "pageSize": { |
| 490 "description": "Page size is for paging and specifies the ma
ximum number of returned rows.\nPage size should be >= 0. A query returns the de
fault of 1,000 rows.\nThe Analytics Core Reporting API returns a maximum of 10,0
00 rows per\nrequest, no matter how many you ask for. It can also return fewer r
ows\nthan requested, if there aren't as many dimension segments as you expect.\n
For instance, there are fewer than 300 possible values for `ga:country`,\nso whe
n segmenting only by country, you can't get more than 300 rows,\neven if you set
`pageSize` to a higher value.", | 490 "description": "Page size is for paging and specifies the ma
ximum number of returned rows.\nPage size should be >= 0. A query returns the de
fault of 1,000 rows.\nThe Analytics Core Reporting API returns a maximum of 10,0
00 rows per\nrequest, no matter how many you ask for. It can also return fewer r
ows\nthan requested, if there aren't as many dimension segments as you expect.\n
For instance, there are fewer than 300 possible values for `ga:country`,\nso whe
n segmenting only by country, you can't get more than 300 rows,\neven if you set
`pageSize` to a higher value.", |
| 491 "format": "int32", | 491 "format": "int32", |
| 492 "type": "integer" | 492 "type": "integer" |
| 493 }, | 493 }, |
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| 876 "type": "array" | 876 "type": "array" |
| 877 } | 877 } |
| 878 }, | 878 }, |
| 879 "type": "object" | 879 "type": "object" |
| 880 }, | 880 }, |
| 881 "Pivot": { | 881 "Pivot": { |
| 882 "description": "The Pivot describes the pivot section in the request
.\nThe Pivot helps rearrange the information in the table for certain reports\nb
y pivoting your data on a second dimension.", | 882 "description": "The Pivot describes the pivot section in the request
.\nThe Pivot helps rearrange the information in the table for certain reports\nb
y pivoting your data on a second dimension.", |
| 883 "id": "Pivot", | 883 "id": "Pivot", |
| 884 "properties": { | 884 "properties": { |
| 885 "dimensions": { | 885 "dimensions": { |
| 886 "description": "A list of dimensions to show as pivot column
s.", | 886 "description": "A list of dimensions to show as pivot column
s. A Pivot can have a maximum\nof 4 dimensions.", |
| 887 "items": { | 887 "items": { |
| 888 "$ref": "Dimension" | 888 "$ref": "Dimension" |
| 889 }, | 889 }, |
| 890 "type": "array" | 890 "type": "array" |
| 891 }, | 891 }, |
| 892 "metrics": { | 892 "metrics": { |
| 893 "description": "Metrics to aggregate and return.", | 893 "description": "The pivot metrics. Pivot metrics are part of
the\nrestriction on total number of metrics in the request.", |
| 894 "items": { | 894 "items": { |
| 895 "$ref": "Metric" | 895 "$ref": "Metric" |
| 896 }, | 896 }, |
| 897 "type": "array" | 897 "type": "array" |
| 898 }, | 898 }, |
| 899 "maxGroupCount": { | 899 "maxGroupCount": { |
| 900 "description": "Specifies the maximum number of groups to re
turn.\nThe default value is 10, also the maximum value is 1,000.", | 900 "description": "Specifies the maximum number of groups to re
turn.\nThe default value is 10, also the maximum value is 1,000.", |
| 901 "format": "int32", | 901 "format": "int32", |
| 902 "type": "integer" | 902 "type": "integer" |
| 903 }, | 903 }, |
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| 1010 "description": "List of metrics for each requested DateRange
.", | 1010 "description": "List of metrics for each requested DateRange
.", |
| 1011 "items": { | 1011 "items": { |
| 1012 "$ref": "DateRangeValues" | 1012 "$ref": "DateRangeValues" |
| 1013 }, | 1013 }, |
| 1014 "type": "array" | 1014 "type": "array" |
| 1015 } | 1015 } |
| 1016 }, | 1016 }, |
| 1017 "type": "object" | 1017 "type": "object" |
| 1018 }, | 1018 }, |
| 1019 "CohortGroup": { | 1019 "CohortGroup": { |
| 1020 "description": "Defines a cohort group.\nFor example:\n\n \"cohor
tGroup\": {\n \"cohorts\": [{\n \"name\": \"cohort 1\",\n \"t
ype\": \"FIRST_VISIT_DATE\",\n \"dateRange\": { \"startDate\": \"2015-08-
01\", \"endDate\": \"2015-08-01\" }\n },{\n \"name\": \"cohort 2\"\n
\"type\": \"FIRST_VISIT_DATE\"\n \"dateRange\": { \"startDate\"
: \"2015-07-01\", \"endDate\": \"2015-07-01\" }\n }]\n }\n", | 1020 "description": "Defines a cohort group.\nFor example:\n\n \"cohor
tGroup\": {\n \"cohorts\": [{\n \"name\": \"cohort 1\",\n \"t
ype\": \"FIRST_VISIT_DATE\",\n \"dateRange\": { \"startDate\": \"2015-08-
01\", \"endDate\": \"2015-08-01\" }\n },{\n \"name\": \"cohort 2\"\n
\"type\": \"FIRST_VISIT_DATE\"\n \"dateRange\": { \"startDate\"
: \"2015-07-01\", \"endDate\": \"2015-07-01\" }\n }]\n }", |
| 1021 "id": "CohortGroup", | 1021 "id": "CohortGroup", |
| 1022 "properties": { | 1022 "properties": { |
| 1023 "lifetimeValue": { | 1023 "lifetimeValue": { |
| 1024 "description": "Enable Life Time Value (LTV). LTV measures
lifetime value for users\nacquired through different channels.\nPlease see:\n[Co
hort Analysis](https://support.google.com/analytics/answer/6074676) and\n[Lifeti
me Value](https://support.google.com/analytics/answer/6182550)\nIf the value of
lifetimeValue is false:\n\n- The metric values are similar to the values in the
web interface cohort\n report.\n- The cohort definition date ranges must be ali
gned to the calendar week\n and month. i.e. while requesting `ga:cohortNthWeek`
the `startDate` in\n the cohort definition should be a Sunday and the `endDate
` should be the\n following Saturday, and for `ga:cohortNthMonth`, the `startDa
te`\n should be the 1st of the month and `endDate` should be the last day\n of
the month.\n\nWhen the lifetimeValue is true:\n\n- The metric values will corre
spond to the values in the web interface\n LifeTime value report.\n- The Lifeti
me Value report shows you how user value (Revenue) and\n engagement (Appviews,
Goal Completions, Sessions, and Session Duration)\n grow during the 90 days aft
er a user is acquired.\n- The metrics are calculated as a cumulative average per
user per the time\n increment.\n- The cohort definition date ranges need not b
e aligned to the calendar\n week and month boundaries.\n- The `viewId` must be
an\n [app view ID](https://support.google.com/analytics/answer/2649553#WebVersu
sAppViews)", | 1024 "description": "Enable Life Time Value (LTV). LTV measures
lifetime value for users\nacquired through different channels.\nPlease see:\n[Co
hort Analysis](https://support.google.com/analytics/answer/6074676) and\n[Lifeti
me Value](https://support.google.com/analytics/answer/6182550)\nIf the value of
lifetimeValue is false:\n\n- The metric values are similar to the values in the
web interface cohort\n report.\n- The cohort definition date ranges must be ali
gned to the calendar week\n and month. i.e. while requesting `ga:cohortNthWeek`
the `startDate` in\n the cohort definition should be a Sunday and the `endDate
` should be the\n following Saturday, and for `ga:cohortNthMonth`, the `startDa
te`\n should be the 1st of the month and `endDate` should be the last day\n of
the month.\n\nWhen the lifetimeValue is true:\n\n- The metric values will corre
spond to the values in the web interface\n LifeTime value report.\n- The Lifeti
me Value report shows you how user value (Revenue) and\n engagement (Appviews,
Goal Completions, Sessions, and Session Duration)\n grow during the 90 days aft
er a user is acquired.\n- The metrics are calculated as a cumulative average per
user per the time\n increment.\n- The cohort definition date ranges need not b
e aligned to the calendar\n week and month boundaries.\n- The `viewId` must be
an\n [app view ID](https://support.google.com/analytics/answer/2649553#WebVersu
sAppViews)", |
| 1025 "type": "boolean" | 1025 "type": "boolean" |
| 1026 }, | 1026 }, |
| 1027 "cohorts": { | 1027 "cohorts": { |
| 1028 "description": "The definition for the cohort.", | 1028 "description": "The definition for the cohort.", |
| 1029 "items": { | 1029 "items": { |
| 1030 "$ref": "Cohort" | 1030 "$ref": "Cohort" |
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| 1110 "type": "string" | 1110 "type": "string" |
| 1111 }, | 1111 }, |
| 1112 "not": { | 1112 "not": { |
| 1113 "description": "Logical `NOT` operator. If this boolean is s
et to true, then the matching\nmetric values will be excluded in the report. The
default is false.", | 1113 "description": "Logical `NOT` operator. If this boolean is s
et to true, then the matching\nmetric values will be excluded in the report. The
default is false.", |
| 1114 "type": "boolean" | 1114 "type": "boolean" |
| 1115 } | 1115 } |
| 1116 }, | 1116 }, |
| 1117 "type": "object" | 1117 "type": "object" |
| 1118 }, | 1118 }, |
| 1119 "Dimension": { | 1119 "Dimension": { |
| 1120 "description": "A dimension in the request.", | 1120 "description": "[Dimensions](https://support.google.com/analytics/an
swer/1033861)\nare attributes of your data. For example, the dimension `ga:city`
\nindicates the city, for example, \"Paris\" or \"New York\", from which\na sess
ion originates.", |
| 1121 "id": "Dimension", | 1121 "id": "Dimension", |
| 1122 "properties": { | 1122 "properties": { |
| 1123 "histogramBuckets": { | 1123 "histogramBuckets": { |
| 1124 "description": "If non-empty, we place dimension values into
buckets after string to\nint64. Dimension values that are not the string repres
entation of an\nintegral value will be converted to zero. The bucket values hav
e to be in\nincreasing order. Each bucket is closed on the lower end, and open
on the\nupper end. The \"first\" bucket includes all values less than the first\
nboundary, the \"last\" bucket includes all values up to infinity. Dimension\nva
lues that fall in a bucket get transformed to a new dimension value. For\nexampl
e, if one gives a list of \"0, 1, 3, 4, 7\", then we return the\nfollowing bucke
ts:\n\n- bucket #1: values < 0, dimension value \"<0\"\n- bucket #2: values in [
0,1), dimension value \"0\"\n- bucket #3: values in [1,3), dimension value \"1-2
\"\n- bucket #4: values in [3,4), dimension value \"3\"\n- bucket #5: values in
[4,7), dimension value \"4-6\"\n- bucket #6: values >= 7, dimension value \"7+\"
\n\nNOTE: If you are applying histogram mutation on any dimension, and using\nth
at dimension in sort, you will want to use the sort type\n`HISTOGRAM_BUCKET` for
that purpose. Without that the dimension values\nwill be sorted according to di
ctionary\n(lexicographic) order. For example the ascending dictionary order is:\
n\n \"<50\", \"1001+\", \"121-1000\", \"50-120\"\n\nAnd the ascending `HISTOGR
AM_BUCKET` order is:\n\n \"<50\", \"50-120\", \"121-1000\", \"1001+\"\n\nThe c
lient has to explicitly request `\"orderType\": \"HISTOGRAM_BUCKET\"`\nfor a his
togram-mutated dimension.", | 1124 "description": "If non-empty, we place dimension values into
buckets after string to\nint64. Dimension values that are not the string repres
entation of an\nintegral value will be converted to zero. The bucket values hav
e to be in\nincreasing order. Each bucket is closed on the lower end, and open
on the\nupper end. The \"first\" bucket includes all values less than the first\
nboundary, the \"last\" bucket includes all values up to infinity. Dimension\nva
lues that fall in a bucket get transformed to a new dimension value. For\nexampl
e, if one gives a list of \"0, 1, 3, 4, 7\", then we return the\nfollowing bucke
ts:\n\n- bucket #1: values < 0, dimension value \"<0\"\n- bucket #2: values in [
0,1), dimension value \"0\"\n- bucket #3: values in [1,3), dimension value \"1-2
\"\n- bucket #4: values in [3,4), dimension value \"3\"\n- bucket #5: values in
[4,7), dimension value \"4-6\"\n- bucket #6: values >= 7, dimension value \"7+\"
\n\nNOTE: If you are applying histogram mutation on any dimension, and using\nth
at dimension in sort, you will want to use the sort type\n`HISTOGRAM_BUCKET` for
that purpose. Without that the dimension values\nwill be sorted according to di
ctionary\n(lexicographic) order. For example the ascending dictionary order is:\
n\n \"<50\", \"1001+\", \"121-1000\", \"50-120\"\n\nAnd the ascending `HISTOGR
AM_BUCKET` order is:\n\n \"<50\", \"50-120\", \"121-1000\", \"1001+\"\n\nThe c
lient has to explicitly request `\"orderType\": \"HISTOGRAM_BUCKET\"`\nfor a his
togram-mutated dimension.", |
| 1125 "items": { | 1125 "items": { |
| 1126 "format": "int64", | 1126 "format": "int64", |
| 1127 "type": "string" | 1127 "type": "string" |
| 1128 }, | 1128 }, |
| 1129 "type": "array" | 1129 "type": "array" |
| 1130 }, | 1130 }, |
| (...skipping 16 matching lines...) Expand all Loading... |
| 1147 "type": "array" | 1147 "type": "array" |
| 1148 } | 1148 } |
| 1149 }, | 1149 }, |
| 1150 "type": "object" | 1150 "type": "object" |
| 1151 } | 1151 } |
| 1152 }, | 1152 }, |
| 1153 "servicePath": "", | 1153 "servicePath": "", |
| 1154 "title": "Google Analytics Reporting API", | 1154 "title": "Google Analytics Reporting API", |
| 1155 "version": "v4" | 1155 "version": "v4" |
| 1156 } | 1156 } |
| OLD | NEW |