chore(release): bumped version to 1.0.1

Author: Bobgy

CHANGELOG.md

@@ -1,5 +1,40 @@
 # Changelog
 
+### [1.0.1](https://github.com/kubeflow/pipelines/compare/1.0.0...1.0.1) (2020-09-14)
+
+
+### Features
+
+* **manifest:** add support for Standalone KFP on AWS. Fixes [\#4337](https://github.com/kubeflow/pipelines/issues/4337) ([\#4350](https://github.com/kubeflow/pipelines/issues/4350)) ([668a3ec](https://github.com/kubeflow/pipelines/commit/668a3ecbb9de50e9b81a42c00ac8d824ea9616c0))
+* GCP marketplace - preserve install config in configmap and secret ([\#4471](https://github.com/kubeflow/pipelines/issues/4471)) ([d447355](https://github.com/kubeflow/pipelines/commit/d447355a9d0ac177d3c7a0e18a61b2fbb1a2e5c4))
+* **deployment:** Add env/platform-agnostic-pns standalone deployment option ([\#4278](https://github.com/kubeflow/pipelines/issues/4278)) ([ee11f9e](https://github.com/kubeflow/pipelines/commit/ee11f9eb63c0a301c6fc0c42972e27d3aac5ecb9))
+* **deployment:** KFP standalone should keep user data when application deleted ([\#4332](https://github.com/kubeflow/pipelines/issues/4332)) ([6e1ceb7](https://github.com/kubeflow/pipelines/commit/6e1ceb7d2208667a5db9d495481f5f970b6cf65c))
+* **sdk:** support HTTP/S PROXY for SDK client  ([\#4215](https://github.com/kubeflow/pipelines/issues/4215)) ([9225b75](https://github.com/kubeflow/pipelines/commit/9225b75006e87a59f968ca10b0a8abd0776e4b1d))
+
+
+### Bug Fixes
+
+* **backend:** add `MaxCallRecvMsgSize(math.MaxInt32)` to proxy server ([\#4402](https://github.com/kubeflow/pipelines/issues/4402)) ([62bed1b](https://github.com/kubeflow/pipelines/commit/62bed1b5d1f156361815321d9a9cf10f4a01921e))
+* **backend:** Add a permission to create events to argo-role ([\#4449](https://github.com/kubeflow/pipelines/issues/4449)) ([2b48697](https://github.com/kubeflow/pipelines/commit/2b4869777060a83822eec7a0855fd914ceca0a43))
+* **backend:** Backend - Cache - Fixed reinstallation. Fixes [\#4299](https://github.com/kubeflow/pipelines/issues/4299) ([\#4320](https://github.com/kubeflow/pipelines/issues/4320)) ([f5e9901](https://github.com/kubeflow/pipelines/commit/f5e9901a107bf6c309018b2214fbbc17086a5128))
+* **backend:** Caching - Only send cache-enabled pods to the caching webhook ([\#4429](https://github.com/kubeflow/pipelines/issues/4429)) ([f2ed52d](https://github.com/kubeflow/pipelines/commit/f2ed52dc9d221fd082dff11b5a2f2252d738da84))
+* **backend:** Caching - Reduced the cache webhook timeout ([\#4428](https://github.com/kubeflow/pipelines/issues/4428)) ([eb86087](https://github.com/kubeflow/pipelines/commit/eb860872b5d048b26fa5e2f0034f97bc7074545c))
+* **backend:** fix typo in reference key type ([\#4376](https://github.com/kubeflow/pipelines/issues/4376)) ([e5f8209](https://github.com/kubeflow/pipelines/commit/e5f82090317ff62f9e25fbf3e9c886b7c4a5fed6))
+* **backend:** logs error when failing to init mysql. Fixes [\#4334](https://github.com/kubeflow/pipelines/issues/4334) ([\#4335](https://github.com/kubeflow/pipelines/issues/4335)) ([64c377e](https://github.com/kubeflow/pipelines/commit/64c377edad636620c451c95a67f510f7a09a613f))
+* **backend:** persistence agent - workflow not found error should be a permanent error ([\#4486](https://github.com/kubeflow/pipelines/issues/4486)) ([c31a346](https://github.com/kubeflow/pipelines/commit/c31a3469d540e1c8f9baae60cec0faec3884d6b5))
+* **backend:** prevent seg fault if workflow manifest is deleted. Fixes [\#4389](https://github.com/kubeflow/pipelines/issues/4389) ([\#4439](https://github.com/kubeflow/pipelines/issues/4439)) ([9f124d6](https://github.com/kubeflow/pipelines/commit/9f124d6a653ccf01ff058d590edbcf7de7f3dfcf))
+* **backend:** reduce confusing ReadArtifact errors for metrics in api server. Fixes [\#3699](https://github.com/kubeflow/pipelines/issues/3699) ([\#4338](https://github.com/kubeflow/pipelines/issues/4338)) ([44cd005](https://github.com/kubeflow/pipelines/commit/44cd005ff4e253b710492ad2607d226946096610))
+* **backend:** skip reporting native Argo workflows which do not have Run ID label. Fixes [\#3584](https://github.com/kubeflow/pipelines/issues/3584) ([\#4438](https://github.com/kubeflow/pipelines/issues/4438)) ([f39a98d](https://github.com/kubeflow/pipelines/commit/f39a98d3cb01eff2e4f4acbceb2867f99911b2f4))
+* **sdk/client:** reserve the host protocal (http or https) so that http host can work. Fixes [\#4277](https://github.com/kubeflow/pipelines/issues/4277) ([\#4285](https://github.com/kubeflow/pipelines/issues/4285)) ([522977f](https://github.com/kubeflow/pipelines/commit/522977fde98265fb5c5000b537592b4bee16b30c))
+* all big enough ui proxy requests fail with error proxying with partial data ([\#4266](https://github.com/kubeflow/pipelines/issues/4266)) ([3a93080](https://github.com/kubeflow/pipelines/commit/3a930807ce056e2c1ed2cfcae0b5d0773844c453))
+* **cache:** adds certificate approver permission to kubeflow-pipelines-cache-deployer-role. Fixes [\#4138](https://github.com/kubeflow/pipelines/issues/4138) ([\#4246](https://github.com/kubeflow/pipelines/issues/4246)) ([0ba88b0](https://github.com/kubeflow/pipelines/commit/0ba88b0709077b0e35d0da59f487471fdec7740c))
+
+
+### Other Pull Requests
+
+* Reduce ttl of persisted final workflow to 1 day ([\#4005](https://github.com/kubeflow/pipelines/issues/4005)) ([135715d](https://github.com/kubeflow/pipelines/commit/135715dbecf7a077c468bf9c3b58e45de101e991))
+* Manifests - Added permissions for certificate approval ([\#4385](https://github.com/kubeflow/pipelines/issues/4385)) ([1445576](https://github.com/kubeflow/pipelines/commit/1445576416acf3beefa4d600fb86b27e5d221d07))
+
 ### [1.0.1-rc.1](https://github.com/kubeflow/pipelines/compare/1.0.0...1.0.1-rc.1) (2020-09-08)
 
 

VERSION

@@ -1 +1 @@
-1.0.1-rc.1
+1.0.1

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: 1.0.1-rc.1
-- Package version: 1.0.1-rc.1
+- API version: 1.0.1
+- Package version: 1.0.1
 - Build package: org.openapitools.codegen.languages.PythonClientCodegen
 For more information, please visit [https://www.google.com](https://www.google.com)
 

backend/api/python_http_client/kfp_server_api/__init__.py

@@ -28,7 +28,7 @@
 
 from __future__ import absolute_import
 
-__version__ = "1.0.1-rc.1"
+__version__ = "1.0.1"
 
 # import apis into sdk package
 from kfp_server_api.api.experiment_service_api import ExperimentServiceApi

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/1.0.1-rc.1/python'
+        self.user_agent = 'OpenAPI-Generator/1.0.1/python'
         self.client_side_validation = configuration.client_side_validation
 
     def __enter__(self):

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: 1.0.1-rc.1\n"\
-               "SDK Package Version: 1.0.1-rc.1".\
+               "Version of the API: 1.0.1\n"\
+               "SDK Package Version: 1.0.1".\
                format(env=sys.platform, pyversion=sys.version)
 
     def get_host_settings(self):

backend/api/python_http_client/setup.py

@@ -27,7 +27,7 @@
 from setuptools import setup, find_packages  # noqa: H301
 
 NAME = "kfp-server-api"
-VERSION = "1.0.1-rc.1"
+VERSION = "1.0.1"
 # To install the library, run the following
 #
 # python setup.py install

backend/api/swagger/kfp_api_single_file.swagger.json

@@ -35,7 +35,9 @@ go_library(
         "@com_github_pkg_errors//:go_default_library",
         "@io_k8s_api//core/v1:go_default_library",
         "@io_k8s_api//policy/v1beta1:go_default_library",
+        "@io_k8s_apimachinery//pkg/api/errors:go_default_library",
         "@io_k8s_apimachinery//pkg/apis/meta/v1:go_default_library",
+        "@io_k8s_apimachinery//pkg/runtime/schema:go_default_library",
         "@io_k8s_apimachinery//pkg/types:go_default_library",
         "@io_k8s_apimachinery//pkg/watch:go_default_library",
         "@io_k8s_client_go//kubernetes:go_default_library",

backend/src/apiserver/client/BUILD.bazel

@@ -54,6 +54,7 @@ go_test(
         "@com_github_pkg_errors//:go_default_library",
         "@com_github_spf13_viper//:go_default_library",
         "@com_github_stretchr_testify//assert:go_default_library",
+        "@com_github_stretchr_testify//require:go_default_library",
         "@io_bazel_rules_go//proto/wkt:timestamp_go_proto",
         "@io_k8s_apimachinery//pkg/apis/meta/v1:go_default_library",
         "@io_k8s_apimachinery//pkg/types:go_default_library",

backend/src/apiserver/resource/BUILD.bazel

@@ -85,7 +85,7 @@ KFP_PACKAGE = 'https://storage.googleapis.com/ml-pipeline/release/0.1.14/kfp.tar
 import kfp.components as comp
 
 bigquery_query_op = comp.load_component_from_url(
-    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1-rc.1/components/gcp/bigquery/query/component.yaml')
+    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/bigquery/query/component.yaml')
 help(bigquery_query_op)
 ```
 

components/gcp/bigquery/query/README.md

@@ -59,7 +59,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1-rc.1
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.bigquery, query,

components/gcp/bigquery/query/component.yaml

@@ -104,7 +104,7 @@
     "import kfp.components as comp\n",
     "\n",
     "bigquery_query_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1-rc.1/components/gcp/bigquery/query/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/bigquery/query/component.yaml')\n",
     "help(bigquery_query_op)"
    ]
   },

components/gcp/bigquery/query/sample.ipynb

@@ -15,7 +15,7 @@
 from setuptools import setup
 
 PACKAGE_NAME = 'kfp-component'
-VERSION = '1.0.1-rc.1'
+VERSION = '1.0.1'
 
 setup(
     name=PACKAGE_NAME,

components/gcp/container/component_sdk/python/setup.py

@@ -91,7 +91,7 @@ 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/1.0.1-rc.1/components/gcp/dataflow/launch_python/component.yaml')
+    dataflow_python_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataflow/launch_python/component.yaml')
     help(dataflow_python_op)
     ```
 

components/gcp/dataflow/launch_python/README.md

@@ -53,7 +53,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1-rc.1
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataflow, launch_python,

components/gcp/dataflow/launch_python/component.yaml

@@ -92,7 +92,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataflow_python_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1-rc.1/components/gcp/dataflow/launch_python/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataflow/launch_python/component.yaml')\n",
     "help(dataflow_python_op)"
    ]
   },

components/gcp/dataflow/launch_python/sample.ipynb

@@ -64,7 +64,7 @@ KFP_PACKAGE = 'https://storage.googleapis.com/ml-pipeline/release/0.1.14/kfp.tar
 import kfp.components as comp
 
 dataflow_template_op = comp.load_component_from_url(
-    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1-rc.1/components/gcp/dataflow/launch_template/component.yaml')
+    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataflow/launch_template/component.yaml')
 help(dataflow_template_op)
 ```
 

components/gcp/dataflow/launch_template/README.md

@@ -63,7 +63,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1-rc.1
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataflow, launch_template,

components/gcp/dataflow/launch_template/component.yaml

@@ -82,7 +82,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataflow_template_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1-rc.1/components/gcp/dataflow/launch_template/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataflow/launch_template/component.yaml')\n",
     "help(dataflow_template_op)"
    ]
   },

components/gcp/dataflow/launch_template/sample.ipynb

@@ -88,7 +88,7 @@ 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/1.0.1-rc.1/components/gcp/dataproc/create_cluster/component.yaml')
+    dataproc_create_cluster_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataproc/create_cluster/component.yaml')
     help(dataproc_create_cluster_op)
     ```
 

components/gcp/dataproc/create_cluster/README.md

@@ -70,7 +70,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1-rc.1
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, create_cluster,

components/gcp/dataproc/create_cluster/component.yaml

@@ -88,7 +88,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_create_cluster_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1-rc.1/components/gcp/dataproc/create_cluster/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataproc/create_cluster/component.yaml')\n",
     "help(dataproc_create_cluster_op)"
    ]
   },

components/gcp/dataproc/create_cluster/sample.ipynb

@@ -66,7 +66,7 @@ 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/1.0.1-rc.1/components/gcp/dataproc/delete_cluster/component.yaml')
+    dataproc_delete_cluster_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataproc/delete_cluster/component.yaml')
     help(dataproc_delete_cluster_op)
     ```
 

components/gcp/dataproc/delete_cluster/README.md

@@ -36,7 +36,7 @@ inputs:
     type: Integer
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1-rc.1
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1
     args: [
       kfp_component.google.dataproc, delete_cluster,
       --project_id, {inputValue: project_id},

components/gcp/dataproc/delete_cluster/component.yaml

@@ -71,7 +71,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_delete_cluster_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1-rc.1/components/gcp/dataproc/delete_cluster/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataproc/delete_cluster/component.yaml')\n",
     "help(dataproc_delete_cluster_op)"
    ]
   },

components/gcp/dataproc/delete_cluster/sample.ipynb

@@ -83,7 +83,7 @@ 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/1.0.1-rc.1/components/gcp/dataproc/submit_hadoop_job/component.yaml')
+    dataproc_submit_hadoop_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataproc/submit_hadoop_job/component.yaml')
     help(dataproc_submit_hadoop_job_op)
     ```
 

components/gcp/dataproc/submit_hadoop_job/README.md

@@ -80,7 +80,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1-rc.1
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, submit_hadoop_job,

components/gcp/dataproc/submit_hadoop_job/component.yaml

@@ -86,7 +86,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_submit_hadoop_job_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1-rc.1/components/gcp/dataproc/submit_hadoop_job/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataproc/submit_hadoop_job/component.yaml')\n",
     "help(dataproc_submit_hadoop_job_op)"
    ]
   },

components/gcp/dataproc/submit_hadoop_job/sample.ipynb

@@ -73,7 +73,7 @@ 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/1.0.1-rc.1/components/gcp/dataproc/submit_hive_job/component.yaml')
+    dataproc_submit_hive_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataproc/submit_hive_job/component.yaml')
     help(dataproc_submit_hive_job_op)
     ```
 

components/gcp/dataproc/submit_hive_job/README.md

@@ -75,7 +75,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1-rc.1
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, submit_hive_job,

components/gcp/dataproc/submit_hive_job/component.yaml

@@ -77,7 +77,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_submit_hive_job_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1-rc.1/components/gcp/dataproc/submit_hive_job/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataproc/submit_hive_job/component.yaml')\n",
     "help(dataproc_submit_hive_job_op)"
    ]
   },

components/gcp/dataproc/submit_hive_job/sample.ipynb

@@ -82,7 +82,7 @@ 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/1.0.1-rc.1/components/gcp/dataproc/submit_pig_job/component.yaml')
+    dataproc_submit_pig_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataproc/submit_pig_job/component.yaml')
     help(dataproc_submit_pig_job_op)
     ```
 

components/gcp/dataproc/submit_pig_job/README.md

@@ -75,7 +75,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1-rc.1
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, submit_pig_job,

components/gcp/dataproc/submit_pig_job/component.yaml

@@ -80,7 +80,7 @@
     "import kfp.components as comp\n",
     "\n",
     "dataproc_submit_pig_job_op = comp.load_component_from_url(\n",
-    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1-rc.1/components/gcp/dataproc/submit_pig_job/component.yaml')\n",
+    "    'https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataproc/submit_pig_job/component.yaml')\n",
     "help(dataproc_submit_pig_job_op)"
    ]
   },

components/gcp/dataproc/submit_pig_job/sample.ipynb

@@ -79,7 +79,7 @@ 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/1.0.1-rc.1/components/gcp/dataproc/submit_pyspark_job/component.yaml')
+    dataproc_submit_pyspark_job_op = comp.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/1.0.1/components/gcp/dataproc/submit_pyspark_job/component.yaml')
     help(dataproc_submit_pyspark_job_op)
     ```
 

components/gcp/dataproc/submit_pyspark_job/README.md

@@ -69,7 +69,7 @@ outputs:
     type: UI metadata
 implementation:
   container:
-    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1-rc.1
+    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.0.1
     args: [
       --ui_metadata_path, {outputPath: MLPipeline UI metadata},
       kfp_component.google.dataproc, submit_pyspark_job,