feat(bigquery): update the api

#### bigquery:v2

The following keys were added:
- schemas.TrainingOptions.properties.autoArimaMinOrder (Total Keys: 2)

Author: yoshi-automation

docs/dyn/bigquery_v2.models.html

@@ -656,7 +656,8 @@ <h3>Method Details</h3>
       &quot;hparams&quot;: { # Options used in model training. # The hyperprameters selected for this trial.
         &quot;adjustStepChanges&quot;: True or False, # If true, detect step changes and make data adjustment in the input time series.
         &quot;autoArima&quot;: True or False, # Whether to enable auto ARIMA or not.
-        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of non-seasonal p and q.
+        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of the sum of non-seasonal p and q.
+        &quot;autoArimaMinOrder&quot;: &quot;A String&quot;, # The min value of the sum of non-seasonal p and q.
         &quot;batchSize&quot;: &quot;A String&quot;, # Batch size for dnn models.
         &quot;boosterType&quot;: &quot;A String&quot;, # Booster type for boosted tree models.
         &quot;calculatePValues&quot;: True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
@@ -967,7 +968,8 @@ <h3>Method Details</h3>
       &quot;trainingOptions&quot;: { # Options used in model training. # Output only. Options that were used for this training run, includes user specified and default options that were used.
         &quot;adjustStepChanges&quot;: True or False, # If true, detect step changes and make data adjustment in the input time series.
         &quot;autoArima&quot;: True or False, # Whether to enable auto ARIMA or not.
-        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of non-seasonal p and q.
+        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of the sum of non-seasonal p and q.
+        &quot;autoArimaMinOrder&quot;: &quot;A String&quot;, # The min value of the sum of non-seasonal p and q.
         &quot;batchSize&quot;: &quot;A String&quot;, # Batch size for dnn models.
         &quot;boosterType&quot;: &quot;A String&quot;, # Booster type for boosted tree models.
         &quot;calculatePValues&quot;: True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
@@ -1605,7 +1607,8 @@ <h3>Method Details</h3>
           &quot;hparams&quot;: { # Options used in model training. # The hyperprameters selected for this trial.
             &quot;adjustStepChanges&quot;: True or False, # If true, detect step changes and make data adjustment in the input time series.
             &quot;autoArima&quot;: True or False, # Whether to enable auto ARIMA or not.
-            &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of non-seasonal p and q.
+            &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of the sum of non-seasonal p and q.
+            &quot;autoArimaMinOrder&quot;: &quot;A String&quot;, # The min value of the sum of non-seasonal p and q.
             &quot;batchSize&quot;: &quot;A String&quot;, # Batch size for dnn models.
             &quot;boosterType&quot;: &quot;A String&quot;, # Booster type for boosted tree models.
             &quot;calculatePValues&quot;: True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
@@ -1916,7 +1919,8 @@ <h3>Method Details</h3>
           &quot;trainingOptions&quot;: { # Options used in model training. # Output only. Options that were used for this training run, includes user specified and default options that were used.
             &quot;adjustStepChanges&quot;: True or False, # If true, detect step changes and make data adjustment in the input time series.
             &quot;autoArima&quot;: True or False, # Whether to enable auto ARIMA or not.
-            &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of non-seasonal p and q.
+            &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of the sum of non-seasonal p and q.
+            &quot;autoArimaMinOrder&quot;: &quot;A String&quot;, # The min value of the sum of non-seasonal p and q.
             &quot;batchSize&quot;: &quot;A String&quot;, # Batch size for dnn models.
             &quot;boosterType&quot;: &quot;A String&quot;, # Booster type for boosted tree models.
             &quot;calculatePValues&quot;: True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
@@ -2567,7 +2571,8 @@ <h3>Method Details</h3>
       &quot;hparams&quot;: { # Options used in model training. # The hyperprameters selected for this trial.
         &quot;adjustStepChanges&quot;: True or False, # If true, detect step changes and make data adjustment in the input time series.
         &quot;autoArima&quot;: True or False, # Whether to enable auto ARIMA or not.
-        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of non-seasonal p and q.
+        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of the sum of non-seasonal p and q.
+        &quot;autoArimaMinOrder&quot;: &quot;A String&quot;, # The min value of the sum of non-seasonal p and q.
         &quot;batchSize&quot;: &quot;A String&quot;, # Batch size for dnn models.
         &quot;boosterType&quot;: &quot;A String&quot;, # Booster type for boosted tree models.
         &quot;calculatePValues&quot;: True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
@@ -2878,7 +2883,8 @@ <h3>Method Details</h3>
       &quot;trainingOptions&quot;: { # Options used in model training. # Output only. Options that were used for this training run, includes user specified and default options that were used.
         &quot;adjustStepChanges&quot;: True or False, # If true, detect step changes and make data adjustment in the input time series.
         &quot;autoArima&quot;: True or False, # Whether to enable auto ARIMA or not.
-        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of non-seasonal p and q.
+        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of the sum of non-seasonal p and q.
+        &quot;autoArimaMinOrder&quot;: &quot;A String&quot;, # The min value of the sum of non-seasonal p and q.
         &quot;batchSize&quot;: &quot;A String&quot;, # Batch size for dnn models.
         &quot;boosterType&quot;: &quot;A String&quot;, # Booster type for boosted tree models.
         &quot;calculatePValues&quot;: True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
@@ -3504,7 +3510,8 @@ <h3>Method Details</h3>
       &quot;hparams&quot;: { # Options used in model training. # The hyperprameters selected for this trial.
         &quot;adjustStepChanges&quot;: True or False, # If true, detect step changes and make data adjustment in the input time series.
         &quot;autoArima&quot;: True or False, # Whether to enable auto ARIMA or not.
-        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of non-seasonal p and q.
+        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of the sum of non-seasonal p and q.
+        &quot;autoArimaMinOrder&quot;: &quot;A String&quot;, # The min value of the sum of non-seasonal p and q.
         &quot;batchSize&quot;: &quot;A String&quot;, # Batch size for dnn models.
         &quot;boosterType&quot;: &quot;A String&quot;, # Booster type for boosted tree models.
         &quot;calculatePValues&quot;: True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
@@ -3815,7 +3822,8 @@ <h3>Method Details</h3>
       &quot;trainingOptions&quot;: { # Options used in model training. # Output only. Options that were used for this training run, includes user specified and default options that were used.
         &quot;adjustStepChanges&quot;: True or False, # If true, detect step changes and make data adjustment in the input time series.
         &quot;autoArima&quot;: True or False, # Whether to enable auto ARIMA or not.
-        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of non-seasonal p and q.
+        &quot;autoArimaMaxOrder&quot;: &quot;A String&quot;, # The max value of the sum of non-seasonal p and q.
+        &quot;autoArimaMinOrder&quot;: &quot;A String&quot;, # The min value of the sum of non-seasonal p and q.
         &quot;batchSize&quot;: &quot;A String&quot;, # Batch size for dnn models.
         &quot;boosterType&quot;: &quot;A String&quot;, # Booster type for boosted tree models.
         &quot;calculatePValues&quot;: True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.

googleapiclient/discovery_cache/documents/bigquery.v2.json

@@ -1710,7 +1710,7 @@
       }
     }
   },
-  "revision": "20230401",
+  "revision": "20230408",
   "rootUrl": "https://bigquery.googleapis.com/",
   "schemas": {
     "AggregateClassificationMetrics": {
@@ -6947,7 +6947,12 @@
           "type": "boolean"
         },
         "autoArimaMaxOrder": {
-          "description": "The max value of non-seasonal p and q.",
+          "description": "The max value of the sum of non-seasonal p and q.",
+          "format": "int64",
+          "type": "string"
+        },
+        "autoArimaMinOrder": {
+          "description": "The min value of the sum of non-seasonal p and q.",
           "format": "int64",
           "type": "string"
         },