Merge branch 'main' into app-deployment

.github/workflows/maven-build-skip.yml

@@ -12,7 +12,7 @@
 # Avoid running Maven CI on each PR opened which does not modify Java or UI code
 # https://docs.github.com/en/repositories/configuring-branches-and-merges-in-your-repository/defining-the-mergeability-
 # of-pull-requests/troubleshooting-required-status-checks#handling-skipped-but-required-checks
-name: Maven CI
+name: Maven MySQL Tests CI
 
 on:
   pull_request_target:

.github/workflows/maven-build.yml

@@ -99,20 +99,11 @@ jobs:
           sudo apt-get install -y unixodbc-dev python3-venv librdkafka-dev gcc libsasl2-dev build-essential libssl-dev libffi-dev \
           librdkafka-dev unixodbc-dev libevent-dev jq
           sudo make install_antlr_cli
-      
-      - name: Build PR with Maven
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        if: ${{ github.event_name == 'pull_request_target' }}
-        run: |
-          git fetch --no-tags https://github.com/open-metadata/OpenMetadata.git +refs/heads/main:refs/remotes/origin/main
-          mvn -pl :openmetadata-service clean package -am
 
       - name: Build with Maven
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        if: ${{ github.event_name == 'push' || github.event_name == 'workflow_dispatch' }}
-        run: mvn -Dsonar.login=${{ secrets.SONAR_TOKEN }} clean package
+        run: mvn clean package -am
 
       - name: Clean Up
         run: |

.github/workflows/maven-postgres-tests-build.yml

@@ -98,20 +98,11 @@ jobs:
           sudo apt-get install -y unixodbc-dev python3-venv librdkafka-dev gcc libsasl2-dev build-essential libssl-dev libffi-dev \
           librdkafka-dev unixodbc-dev libevent-dev jq
           sudo make install_antlr_cli
-      
-      - name: Build PR with Maven
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        if: ${{ github.event_name == 'pull_request_target' }}
-        run: |
-          git fetch --no-tags https://github.com/open-metadata/OpenMetadata.git +refs/heads/main:refs/remotes/origin/main
-          mvn -pl :openmetadata-service -Ppostgres-tests clean package -am
 
       - name: Build with Maven
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        if: ${{ github.event_name == 'push' }}
-        run: mvn clean package
+        run: mvn -Ppostgres-tests clean package -am
 
       - name: Clean Up
         run: |

.github/workflows/maven-sonar-build.yml

@@ -99,20 +99,11 @@ jobs:
           sudo apt-get install -y unixodbc-dev python3-venv librdkafka-dev gcc libsasl2-dev build-essential libssl-dev libffi-dev \
           librdkafka-dev unixodbc-dev libevent-dev jq
           sudo make install_antlr_cli
-      
-      - name: Build PR with Maven
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        if: ${{ github.event_name == 'pull_request_target' }}
-        run: |
-          git fetch --no-tags https://github.com/open-metadata/OpenMetadata.git +refs/heads/main:refs/remotes/origin/main
-          mvn -pl :openmetadata-service -Pstatic-code-analysis clean package -am
 
       - name: Build with Maven
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        if: ${{ github.event_name == 'push' || github.event_name == 'workflow_dispatch' }}
-        run: mvn -Dsonar.login=${{ secrets.SONAR_TOKEN }} -Pstatic-code-analysis -DskipTests clean package
+        run: mvn -Pstatic-code-analysis clean package -am
 
       - name: Clean Up
         run: |

openmetadata-docs/content/v1.2.x/connectors/custom-connectors.md

@@ -20,6 +20,11 @@ We'd recommend to go through the example to better understand how all the pieces
 
 {% /note %}
 
+Watch OpenMetadata's [Webinar on Custom Connectors](https://www.youtube.com/watch?v=fDUj30Ub9VE)
+
+{% youtube videoId="fDUj30Ub9VE" start="0:00" end="36:33" /%}
+
+# Steps to Set Up a Custom Connector
 
 ## Step 1 - Prepare your Connector
 
@@ -31,15 +36,15 @@ In [connector/my_awesome_connector.py](https://github.com/open-metadata/openmeta
 Note how the important method is the `next_record`. This is the generator function that will be iterated over
 to send all the Create Entity Requests to the `Sink`. Read more about the `Workflow` [here](https://docs.open-metadata.org/sdk/python/build-connector).
 
-## Step 2 - Yield the data
+## Step 2 - Yield the Data
 
 The `Sink` is expecting Create Entity Requests. To get familiar with the Python SDK and understand how to create
 the different Entities, a recommended read is the Python SDK [docs](https://docs.open-metadata.org/sdk/python).
 
 We do not have docs and examples of all the supported Services. A way to get examples on how to create and fetch
 other types of Entities is to directly refer to the `ometa` [integration tests](https://github.com/open-metadata/OpenMetadata/tree/main/ingestion/tests/integration/ometa).
 
-## Step 3 - Prepare the package installation
+## Step 3 - Prepare the Package Installation
 
 We'll need to package the code so that it can be shipped to the ingestion container and used there. In this demo
 you can find a simple `setup.py` that builds the `connector` module.
@@ -67,7 +72,7 @@ COPY setup.py .
 RUN pip install --no-deps .
 ```
 
-## Step 5 - Run OpenMetadata with the custom Ingestion image
+## Step 5 - Run OpenMetadata with the Custom Ingestion Image
 
 We have a `Makefile` prepared for you to run `make run`. This will get OpenMetadata up in Docker Compose using the
 custom Ingestion image.

openmetadata-docs/content/v1.2.x/connectors/index.md

@@ -35,64 +35,69 @@ the following docs to run the Ingestion Framework in any orchestrator externally
 - [AzureSQL](/connectors/database/azuresql)
 - [BigQuery](/connectors/database/bigquery)
 - [Clickhouse](/connectors/database/clickhouse)
-- [Databricks SQL](/connectors/database/databricks)
+- [Couchbase](/connectors/database/couchbase)
 - [Data lake](/connectors/database/datalake)
+- [Databricks SQL](/connectors/database/databricks)
 - [DB2](/connectors/database/db2)
 - [Delta Lake](/connectors/database/deltalake)
+- [Domo Database](/connectors/database/domo-database)
 - [Druid](/connectors/database/druid)
 - [DynamoDB](/connectors/database/dynamodb)
 - [Glue](/connectors/database/glue)
+- [Greenplum](/connectors/database/greenplum)
 - [Hive](/connectors/database/hive)
+- [Impala](/connectors/database/impala)
 - [MariaDB](/connectors/database/mariadb)
+- [MongoDB](/connectors/database/mongodb)
 - [MSSQL](/connectors/database/mssql)
 - [MySQL](/connectors/database/mysql)
 - [Oracle](/connectors/database/oracle)
+- [PinotDB](/connectors/database/pinotdb)
 - [Postgres](/connectors/database/postgres)
 - [Presto](/connectors/database/presto)
-- [PinotDB](/connectors/database/pinotdb)
 - [Redshift](/connectors/database/redshift)
 - [Salesforce](/connectors/database/salesforce)
+- [SAP Hana](/connectors/database/sap-hana)
 - [SingleStore](/connectors/database/singlestore)
 - [Snowflake](/connectors/database/snowflake)
 - [SQLite](/connectors/database/sqlite)
 - [Trino](/connectors/database/trino)
 - [Vertica](/connectors/database/vertica)
-- [Domo Database](/connectors/database/domo-database)
 
 ## Dashboard Services
 
+- [Domo Dashboard](/connectors/dashboard/domo-dashboard)
 - [Looker](/connectors/dashboard/looker)
 - [Metabase](/connectors/dashboard/metabase)
 - [Mode](/connectors/dashboard/mode)
 - [PowerBI](/connectors/dashboard/powerbi)
+- [Qlik Sense](/connectors/dashboard/qliksense)
+- [QuickSight](/connectors/dashboard/quicksight)
 - [Redash](/connectors/dashboard/redash)
 - [Superset](/connectors/dashboard/superset)
 - [Tableau](/connectors/dashboard/tableau)
-- [Domo Dashboard](/connectors/dashboard/domo-dashboard)
-- [Qlik Sense](/connectors/dashboard/qliksense)
-- [QuickSight](/connectors/dashboard/quicksight)
 
 ## Messaging Services
 
 - [Kafka](/connectors/messaging/kafka)
-- [Redpanda](/connectors/messaging/redpanda)
 - [Kinesis](/connectors/messaging/kinesis)
-
+- [Redpanda](/connectors/messaging/redpanda)
 
 ## Pipeline Services
 
 - [Airbyte](/connectors/pipeline/airbyte)
 - [Airflow](/connectors/pipeline/airflow)
 - [Dagster](/connectors/pipeline/dagster)
+- [Databricks Pipeline](/connectors/pipeline/databricks-pipeline)
+- [Domo Pipeline](/connectors/pipeline/domo-pipeline)
 - [Fivetran](/connectors/pipeline/fivetran)
 - [Glue](/connectors/pipeline/glue-pipeline)
-- [Domo Pipeline](/connectors/pipeline/domo-pipeline)
 - [NiFi](/connectors/pipeline/nifi)
 - [Spline](/connectors/pipeline/spline)
 
 ## ML Model Services
 
-- [Mlflow](/connectors/ml-model/mlflow)
+- [MLflow](/connectors/ml-model/mlflow)
 - [Sagemaker](/connectors/ml-model/sagemaker)
 
 ## Storage Services
@@ -106,4 +111,4 @@ the following docs to run the Ingestion Framework in any orchestrator externally
 
 ## Search Services
 
-- [ElasticSearch](/connectors/search/elasticsearch)
+- [Elasticsearch](/connectors/search/elasticsearch)

openmetadata-docs/content/v1.2.x/connectors/ml-model/mlflow/index.md

@@ -1,13 +1,13 @@
 ---
-title: Mlflow
+title: MLflow
 slug: /connectors/ml-model/mlflow
 ---
 
-# Mlflow
+# MLflow
 
-In this section, we provide guides and references to use the Mlflow connector.
+In this section, we provide guides and references to use the MLflow connector.
 
-Configure and schedule Mlflow metadata and profiler workflows from the OpenMetadata UI:
+Configure and schedule MLflow metadata and profiler workflows from the OpenMetadata UI:
 
 - [Requirements](#requirements)
 - [Metadata Ingestion](#metadata-ingestion)
@@ -17,7 +17,7 @@ Configure and schedule Mlflow metadata and profiler workflows from the OpenMetad
 ## Requirements
 
 To extract metadata, OpenMetadata needs two elements:
-- **Tracking URI**: Address of local or remote tracking server. More information on the MLFlow documentation [here](https://www.mlflow.org/docs/latest/tracking.html#where-runs-are-recorded)
+- **Tracking URI**: Address of local or remote tracking server. More information on the MLflow documentation [here](https://www.mlflow.org/docs/latest/tracking.html#where-runs-are-recorded)
 - **Registry URI**: Address of local or remote model registry server.
 
 ## Metadata Ingestion

openmetadata-docs/content/v1.2.x/connectors/ml-model/mlflow/yaml.md

@@ -1,13 +1,13 @@
 ---
-title: Run the Mlflow Connector Externally
+title: Run the MLflow Connector Externally
 slug: /connectors/ml-model/mlflow/yaml
 ---
 
-# Run the Mlflow Connector Externally
+# Run the MLflow Connector Externally
 
-In this section, we provide guides and references to use the Mlflow connector.
+In this section, we provide guides and references to use the MLflow connector.
 
-Configure and schedule Mlflow metadata and profiler workflows from the OpenMetadata UI:
+Configure and schedule MLflow metadata and profiler workflows from the OpenMetadata UI:
 
 - [Requirements](#requirements)
 - [Metadata Ingestion](#metadata-ingestion)
@@ -24,7 +24,7 @@ To deploy OpenMetadata, check the Deployment guides.
 
 ### Python Requirements
 
-To run the Mlflow ingestion, you will need to install:
+To run the MLflow ingestion, you will need to install:
 
 ```bash
 pip3 install "openmetadata-ingestion[mlflow]"
@@ -34,7 +34,7 @@ pip3 install "openmetadata-ingestion[mlflow]"
 
 All connectors are defined as JSON Schemas.
 [Here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/mlmodel/mlflowConnection.json)
-you can find the structure to create a connection to Mlflow.
+you can find the structure to create a connection to MLflow.
 
 In order to create and run a Metadata Ingestion workflow, we will follow
 the steps to create a YAML configuration able to connect to the source,
@@ -45,7 +45,7 @@ The workflow is modeled around the following
 
 ### 1. Define the YAML Config
 
-This is a sample config for Mlflow:
+This is a sample config for MLflow:
 
 {% codePreview %}
 
@@ -55,14 +55,14 @@ This is a sample config for Mlflow:
 
 {% codeInfo srNumber=1 %}
 
-**trackingUri**: Mlflow Experiment tracking URI. E.g., http://localhost:5000
+**trackingUri**: MLflow Experiment tracking URI. E.g., http://localhost:5000
 
 
 {% /codeInfo %}
 
 {% codeInfo srNumber=2 %}
 
-**registryUri**: Mlflow Model registry backend. E.g., mysql+pymysql://mlflow:password@localhost:3307/experiments
+**registryUri**: MLflow Model registry backend. E.g., mysql+pymysql://mlflow:password@localhost:3307/experiments
 
 {% /codeInfo %}
 

openmetadata-docs/content/v1.2.x/connectors/search/elasticsearch/index.md

@@ -1,20 +1,20 @@
 ---
-title: ElasticSearch
+title: Elasticsearch
 slug: /connectors/search/elasticsearch
 ---
 
-# ElasticSearch
+# Elasticsearch
 
 | Feature            | Status               |
 |------------|------------------------------|
 | Search Indexes | {% icon iconName="check" /%} |
 | Sample Data | {% icon iconName="check" /%} |
-| Supported Versions | ElasticSearch 7.0 and above |
+| Supported Versions | Elasticsearch 7.0 and above |
 | Stage              | BETA                      |
 
-In this section, we provide guides and references to use the ElasticSearch connector.
+In this section, we provide guides and references to use the Elasticsearch connector.
 
-Configure and schedule ElasticSearch metadata workflow from the OpenMetadata UI:
+Configure and schedule Elasticsearch metadata workflow from the OpenMetadata UI:
 
 - [Requirements](#requirements)
 - [Metadata Ingestion](#metadata-ingestion)
@@ -23,7 +23,7 @@ Configure and schedule ElasticSearch metadata workflow from the OpenMetadata UI:
 
 ## Requirements
 
-We extract ElasticSearch's metadata by using its [API](https://www.elastic.co/guide/en/elasticsearch/reference/current/rest-apis.html). To run this ingestion, you just need a user with permissions to the ElasticSearch instance.
+We extract Elasticsearch's metadata by using its [API](https://www.elastic.co/guide/en/elasticsearch/reference/current/rest-apis.html). To run this ingestion, you just need a user with permissions to the ElasticSearch instance.
 
 
 ## Metadata Ingestion
@@ -43,13 +43,13 @@ We extract ElasticSearch's metadata by using its [API](https://www.elastic.co/gu
 
 #### Connection Details
 
-- **Host and Port**: This parameter specifies the host and port of the ElasticSearch instance. This should be specified as a URI string in the format `http://hostname:port` or `https://hostname:port`. For example, you might set it to `https://localhost:9200`.
+- **Host and Port**: This parameter specifies the host and port of the Elasticsearch instance. This should be specified as a URI string in the format `http://hostname:port` or `https://hostname:port`. For example, you might set it to `https://localhost:9200`.
 - **Authentication Types**:
     1. Basic Authentication
-    - Username: Username to connect to ElasticSearch required when Basic Authentication is enabled on ElasticSearch.
-    - Password: Password of the user account to connect with ElasticSearch.
+    - Username: Username to connect to Elasticsearch required when Basic Authentication is enabled on Elasticsearch.
+    - Password: Password of the user account to connect with Elasticsearch.
     2. API Key Authentication
-    - API Key: API Key to connect to ElasticSearch required when API Key Authentication is enabled on ElasticSearch.
+    - API Key: API Key to connect to Elasticsearch required when API Key Authentication is enabled on Elasticsearch.
     - API Key Id: Enter API Key ID In case of API Key Authentication if there is any API Key ID associated with the API Key, otherwise this field can be left blank.
 - **SSL Certificates**:
     1. SSL Certificates By Path
@@ -79,7 +79,7 @@ We extract ElasticSearch's metadata by using its [API](https://www.elastic.co/gu
     ```
     -----BEGIN CERTIFICATE-----\nMII..\nMBQ...\nCgU..\n8Lt..\n...\nh+4=\n-----END CERTIFICATE-----\n
 
-- **Connection Timeout in Seconds**: Connection timeout configuration for communicating with ElasticSearch APIs.
+- **Connection Timeout in Seconds**: Connection timeout configuration for communicating with Elasticsearch APIs.
 
 {% /extraContent %}