chore(release): bumped version to 1.2.0

alembiewski · Dec 18, 2020 · 5445ce8 · 5445ce8
1 parent d9fb33c
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,5 +1,25 @@
 # Changelog
 
+## [1.2.0](https://github.com/kubeflow/pipelines/compare/1.1.2...1.2.0) (2020-12-18)
+
+
+### Features
+
+* **components:** Add v1beta1 Katib launcher and samples ([\#4798](https://github.com/kubeflow/pipelines/issues/4798)) ([89e4210](https://github.com/kubeflow/pipelines/commit/89e42105bd941e1d918d0bff9ba0c4f80b106ed4))
+* **sdk:** Add artifact ontology and migrate compiler utils to onboard artifact types ([\#4901](https://github.com/kubeflow/pipelines/issues/4901)) ([2386471](https://github.com/kubeflow/pipelines/commit/2386471cdf18456ec6e5d53d49b2bda74e078a6f))
+* **sdk:** Add settings of the dnsConfig field. Fixes [\#4836](https://github.com/kubeflow/pipelines/issues/4836) ([\#4837](https://github.com/kubeflow/pipelines/issues/4837)) ([5a4b70e](https://github.com/kubeflow/pipelines/commit/5a4b70e37c2c42cb0add0715e4a4037042e9d2d7))
+* **sdk:** allow calling GroupOp.after with multiple ops ([\#4788](https://github.com/kubeflow/pipelines/issues/4788)) ([5169489](https://github.com/kubeflow/pipelines/commit/5169489be5f73797490564685fe46d6bbf64908d))
+* **sdk:** Components - Restored stack traces in lightweight python components. Fixes [\#4273](https://github.com/kubeflow/pipelines/issues/4273), [\#4849](https://github.com/kubeflow/pipelines/issues/4849) ([\#4861](https://github.com/kubeflow/pipelines/issues/4861)) ([7a66414](https://github.com/kubeflow/pipelines/commit/7a66414cf72ba5c746cac7fc6c8ecad67fc5e885))
+* **SDK:** adds Artifact base class. ([\#4895](https://github.com/kubeflow/pipelines/issues/4895)) ([7591805](https://github.com/kubeflow/pipelines/commit/759180537788e01a7906432255ad663c296e9518))
+
+
+### Bug Fixes
+
+* **frontend:** fixed getting executions failure. Fixes [\#4903](https://github.com/kubeflow/pipelines/issues/4903) ([\#4907](https://github.com/kubeflow/pipelines/issues/4907)) ([df7a66f](https://github.com/kubeflow/pipelines/commit/df7a66f3b70dfc41c12fd14554c59c43c8a4dd2f))
+* **frontend:** Use task_display_name annotation when displaying run metrics ([\#4875](https://github.com/kubeflow/pipelines/issues/4875)) ([d4e8b87](https://github.com/kubeflow/pipelines/commit/d4e8b8736c3a468b73916ec5d00760999809d0da))
+* **sdk:** Do not wait for resource deletion ([\#4820](https://github.com/kubeflow/pipelines/issues/4820)) ([8f70bf3](https://github.com/kubeflow/pipelines/commit/8f70bf325ea779980ec1fbd0242b2b646bd6a70c))
+* **sdk:** make healthz exception visible in logs by default ([\#4904](https://github.com/kubeflow/pipelines/issues/4904)) ([44fcda7](https://github.com/kubeflow/pipelines/commit/44fcda7dca23dfdac4ead0195e5c005bb7b15115))
+
 ### [1.1.2](https://github.com/kubeflow/pipelines/compare/0.5.1...1.1.2) (2020-12-14)
 
 

diff --git a/VERSION b/VERSION
@@ -1 +1 @@
-1.1.2
+1.2.0
diff --git a/backend/api/python_http_client/README.md b/backend/api/python_http_client/README.md
@@ -3,8 +3,8 @@ This file contains REST API specification for Kubeflow Pipelines. The file is au
 
 This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
 
-- API version: 1.1.2
-- Package version: 1.1.2
+- API version: 1.2.0
+- Package version: 1.2.0
 - Build package: org.openapitools.codegen.languages.PythonClientCodegen
 For more information, please visit [https://www.google.com](https://www.google.com)
 

diff --git a/backend/api/python_http_client/kfp_server_api/__init__.py b/backend/api/python_http_client/kfp_server_api/__init__.py
@@ -28,7 +28,7 @@
 
 from __future__ import absolute_import
 
-__version__ = "1.1.2"
+__version__ = "1.2.0"
 
 # import apis into sdk package
 from kfp_server_api.api.experiment_service_api import ExperimentServiceApi

diff --git a/backend/api/python_http_client/kfp_server_api/api_client.py b/backend/api/python_http_client/kfp_server_api/api_client.py
@@ -92,7 +92,7 @@ def __init__(self, configuration=None, header_name=None, header_value=None,
             self.default_headers[header_name] = header_value
         self.cookie = cookie
         # Set default User-Agent.
-        self.user_agent = 'OpenAPI-Generator/1.1.2/python'
+        self.user_agent = 'OpenAPI-Generator/1.2.0/python'
         self.client_side_validation = configuration.client_side_validation
 
     def __enter__(self):

diff --git a/backend/api/python_http_client/kfp_server_api/configuration.py b/backend/api/python_http_client/kfp_server_api/configuration.py
@@ -365,8 +365,8 @@ def to_debug_report(self):
         return "Python SDK Debug Report:\n"\
                "OS: {env}\n"\
                "Python Version: {pyversion}\n"\
-               "Version of the API: 1.1.2\n"\
-               "SDK Package Version: 1.1.2".\
+               "Version of the API: 1.2.0\n"\
+               "SDK Package Version: 1.2.0".\
                format(env=sys.platform, pyversion=sys.version)
 
     def get_host_settings(self):

diff --git a/backend/api/python_http_client/setup.py b/backend/api/python_http_client/setup.py
@@ -27,7 +27,7 @@
 from setuptools import setup, find_packages  # noqa: H301
 
 NAME = "kfp-server-api"
-VERSION = "1.1.2"
+VERSION = "1.2.0"
 # To install the library, run the following
 #
 # python setup.py install

diff --git a/backend/api/swagger/kfp_api_single_file.swagger.json b/backend/api/swagger/kfp_api_single_file.swagger.json
diff --git a/components/README.md b/components/README.md
diff --git a/components/gcp/bigquery/query/to_CSV/component.yaml b/components/gcp/bigquery/query/to_CSV/component.yaml
@@ -47,7 +47,7 @@ outputs:
     type: CSV
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path,   {outputPath: MLPipeline UI metadata},
       kfp_component.google.bigquery, query,

diff --git a/components/gcp/bigquery/query/to_gcs/component.yaml b/components/gcp/bigquery/query/to_gcs/component.yaml
@@ -65,7 +65,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.bigquery, query,

diff --git a/components/gcp/bigquery/query/to_table/README.md b/components/gcp/bigquery/query/to_table/README.md
@@ -77,7 +77,7 @@ Note: The following sample code works in an IPython notebook or directly in Pyth
 import kfp.components as comp
 
 bigquery_query_op = comp.load_component_from_url(
-    'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/bigquery/query/to_table/component.yaml')
+    'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/bigquery/query/to_table/component.yaml')
 help(bigquery_query_op)
 ```
 

diff --git a/components/gcp/bigquery/query/to_table/component.yaml b/components/gcp/bigquery/query/to_table/component.yaml
@@ -56,7 +56,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.bigquery, query,

diff --git a/components/gcp/container/component_sdk/python/setup.py b/components/gcp/container/component_sdk/python/setup.py
@@ -15,7 +15,7 @@
 from setuptools import setup
 
 PACKAGE_NAME = 'kfp-component'
-VERSION = '1.1.2'
+VERSION = '1.2.0'
 
 setup(
     name=PACKAGE_NAME,

diff --git a/components/gcp/dataflow/launch_python/README.md b/components/gcp/dataflow/launch_python/README.md
@@ -90,7 +90,7 @@ The steps to use the component in a pipeline are:
     ```python
     import kfp.components as comp
 
-    dataflow_python_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataflow/launch_python/component.yaml')
+    dataflow_python_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataflow/launch_python/component.yaml')
     help(dataflow_python_op)
     ```
 

diff --git a/components/gcp/dataflow/launch_python/component.yaml b/components/gcp/dataflow/launch_python/component.yaml
@@ -53,7 +53,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataflow, launch_python,

diff --git a/components/gcp/dataflow/launch_python/sample.ipynb b/components/gcp/dataflow/launch_python/sample.ipynb
@@ -91,7 +91,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataflow_python_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataflow/launch_python/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataflow/launch_python/component.yaml')\n",
     "help(dataflow_python_op)"
    ]
   },

diff --git a/components/gcp/dataflow/launch_template/README.md b/components/gcp/dataflow/launch_template/README.md
@@ -63,7 +63,7 @@ Follow these steps to use the component in a pipeline:
 import kfp.components as comp
 
 dataflow_template_op = comp.load_component_from_url(
-    'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataflow/launch_template/component.yaml')
+    'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataflow/launch_template/component.yaml')
 help(dataflow_template_op)
 ```
 

diff --git a/components/gcp/dataflow/launch_template/component.yaml b/components/gcp/dataflow/launch_template/component.yaml
@@ -63,7 +63,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataflow, launch_template,

diff --git a/components/gcp/dataflow/launch_template/sample.ipynb b/components/gcp/dataflow/launch_template/sample.ipynb
@@ -81,7 +81,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataflow_template_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataflow/launch_template/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataflow/launch_template/component.yaml')\n",
     "help(dataflow_template_op)"
    ]
   },

diff --git a/components/gcp/dataproc/create_cluster/README.md b/components/gcp/dataproc/create_cluster/README.md
@@ -87,7 +87,7 @@ Follow these steps to use the component in a pipeline:
     ```python
     import kfp.components as comp
 
-    dataproc_create_cluster_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/create_cluster/component.yaml')
+    dataproc_create_cluster_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/create_cluster/component.yaml')
     help(dataproc_create_cluster_op)
     ```
 

diff --git a/components/gcp/dataproc/create_cluster/component.yaml b/components/gcp/dataproc/create_cluster/component.yaml
@@ -70,7 +70,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, create_cluster,

diff --git a/components/gcp/dataproc/create_cluster/sample.ipynb b/components/gcp/dataproc/create_cluster/sample.ipynb
@@ -87,7 +87,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_create_cluster_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/create_cluster/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/create_cluster/component.yaml')\n",
     "help(dataproc_create_cluster_op)"
    ]
   },

diff --git a/components/gcp/dataproc/delete_cluster/README.md b/components/gcp/dataproc/delete_cluster/README.md
@@ -65,7 +65,7 @@ Follow these steps to use the component in a pipeline:
     ```python
     import kfp.components as comp
 
-    dataproc_delete_cluster_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/delete_cluster/component.yaml')
+    dataproc_delete_cluster_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/delete_cluster/component.yaml')
     help(dataproc_delete_cluster_op)
     ```
 

diff --git a/components/gcp/dataproc/delete_cluster/component.yaml b/components/gcp/dataproc/delete_cluster/component.yaml
@@ -36,7 +36,7 @@ inputs:
     type: Integer
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       kfp_component.google.dataproc, delete_cluster,
       --project_id, {inputValue: project_id},

diff --git a/components/gcp/dataproc/delete_cluster/sample.ipynb b/components/gcp/dataproc/delete_cluster/sample.ipynb
@@ -70,7 +70,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_delete_cluster_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/delete_cluster/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/delete_cluster/component.yaml')\n",
     "help(dataproc_delete_cluster_op)"
    ]
   },

diff --git a/components/gcp/dataproc/submit_hadoop_job/README.md b/components/gcp/dataproc/submit_hadoop_job/README.md
@@ -82,7 +82,7 @@ Follow these steps to use the component in a pipeline:
     ```python
     import kfp.components as comp
 
-    dataproc_submit_hadoop_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/submit_hadoop_job/component.yaml')
+    dataproc_submit_hadoop_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/submit_hadoop_job/component.yaml')
     help(dataproc_submit_hadoop_job_op)
     ```
 

diff --git a/components/gcp/dataproc/submit_hadoop_job/component.yaml b/components/gcp/dataproc/submit_hadoop_job/component.yaml
@@ -80,7 +80,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, submit_hadoop_job,

diff --git a/components/gcp/dataproc/submit_hadoop_job/sample.ipynb b/components/gcp/dataproc/submit_hadoop_job/sample.ipynb
@@ -85,7 +85,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_submit_hadoop_job_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/submit_hadoop_job/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/submit_hadoop_job/component.yaml')\n",
     "help(dataproc_submit_hadoop_job_op)"
    ]
   },

diff --git a/components/gcp/dataproc/submit_hive_job/README.md b/components/gcp/dataproc/submit_hive_job/README.md
@@ -72,7 +72,7 @@ Follow these steps to use the component in a pipeline:
     ```python
     import kfp.components as comp
 
-    dataproc_submit_hive_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/submit_hive_job/component.yaml')
+    dataproc_submit_hive_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/submit_hive_job/component.yaml')
     help(dataproc_submit_hive_job_op)
     ```
 

diff --git a/components/gcp/dataproc/submit_hive_job/component.yaml b/components/gcp/dataproc/submit_hive_job/component.yaml
@@ -75,7 +75,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, submit_hive_job,

diff --git a/components/gcp/dataproc/submit_hive_job/sample.ipynb b/components/gcp/dataproc/submit_hive_job/sample.ipynb
@@ -76,7 +76,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_submit_hive_job_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/submit_hive_job/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/submit_hive_job/component.yaml')\n",
     "help(dataproc_submit_hive_job_op)"
    ]
   },

diff --git a/components/gcp/dataproc/submit_pig_job/README.md b/components/gcp/dataproc/submit_pig_job/README.md
@@ -81,7 +81,7 @@ Follow these steps to use the component in a pipeline:
     ```python
     import kfp.components as comp
 
-    dataproc_submit_pig_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/submit_pig_job/component.yaml')
+    dataproc_submit_pig_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/submit_pig_job/component.yaml')
     help(dataproc_submit_pig_job_op)
     ```
 

diff --git a/components/gcp/dataproc/submit_pig_job/component.yaml b/components/gcp/dataproc/submit_pig_job/component.yaml
@@ -75,7 +75,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, submit_pig_job,

diff --git a/components/gcp/dataproc/submit_pig_job/sample.ipynb b/components/gcp/dataproc/submit_pig_job/sample.ipynb
@@ -79,7 +79,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_submit_pig_job_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/submit_pig_job/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/submit_pig_job/component.yaml')\n",
     "help(dataproc_submit_pig_job_op)"
    ]
   },

diff --git a/components/gcp/dataproc/submit_pyspark_job/README.md b/components/gcp/dataproc/submit_pyspark_job/README.md
@@ -78,7 +78,7 @@ Follow these steps to use the component in a pipeline:
     ```python
     import kfp.components as comp
 
-    dataproc_submit_pyspark_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/submit_pyspark_job/component.yaml')
+    dataproc_submit_pyspark_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/submit_pyspark_job/component.yaml')
     help(dataproc_submit_pyspark_job_op)
     ```
 

diff --git a/components/gcp/dataproc/submit_pyspark_job/component.yaml b/components/gcp/dataproc/submit_pyspark_job/component.yaml
@@ -69,7 +69,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, submit_pyspark_job,

diff --git a/components/gcp/dataproc/submit_pyspark_job/sample.ipynb b/components/gcp/dataproc/submit_pyspark_job/sample.ipynb
@@ -81,7 +81,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_submit_pyspark_job_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/submit_pyspark_job/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/submit_pyspark_job/component.yaml')\n",
     "help(dataproc_submit_pyspark_job_op)"
    ]
   },

diff --git a/components/gcp/dataproc/submit_spark_job/README.md b/components/gcp/dataproc/submit_spark_job/README.md
@@ -94,7 +94,7 @@ Follow these steps to use the component in a pipeline:
     import kfp.components as comp
 
     dataproc_submit_spark_job_op = comp.load_component_from_url(
-        'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/submit_spark_job/component.yaml')
+        'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/submit_spark_job/component.yaml')
     help(dataproc_submit_spark_job_op)
     ```
 

diff --git a/components/gcp/dataproc/submit_spark_job/component.yaml b/components/gcp/dataproc/submit_spark_job/component.yaml
@@ -76,7 +76,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, submit_spark_job,

diff --git a/components/gcp/dataproc/submit_spark_job/sample.ipynb b/components/gcp/dataproc/submit_spark_job/sample.ipynb
@@ -92,7 +92,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_submit_spark_job_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/submit_spark_job/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/submit_spark_job/component.yaml')\n",
     "help(dataproc_submit_spark_job_op)"
    ]
   },

diff --git a/components/gcp/dataproc/submit_sparksql_job/README.md b/components/gcp/dataproc/submit_sparksql_job/README.md
@@ -73,7 +73,7 @@ Follow these steps to use the component in a pipeline:
     ```python
     import kfp.components as comp
 
-    dataproc_submit_sparksql_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.1.2/components/gcp/dataproc/submit_sparksql_job/component.yaml')
+    dataproc_submit_sparksql_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.2.0/components/gcp/dataproc/submit_sparksql_job/component.yaml')
     help(dataproc_submit_sparksql_job_op)
     ```
 

diff --git a/components/gcp/dataproc/submit_sparksql_job/component.yaml b/components/gcp/dataproc/submit_sparksql_job/component.yaml
@@ -75,7 +75,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.1.2
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.2.0
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, submit_sparksql_job,