docs: Update references (#372)

* Initial commit

* Update xrefs

* Update xref

docs/modules/hive/pages/getting_started/first_steps.adoc

@@ -1,14 +1,16 @@
 = First steps
 
-After going through the xref:getting_started/installation.adoc[] section and having installed all the operators, you will now deploy a Hive metastore cluster and it's dependencies. Afterwards you can <<_verify_that_it_works, verify that it works>>.
+After going through the xref:getting_started/installation.adoc[] section and having installed all the operators, you
+will now deploy a Hive metastore cluster and it's dependencies. Afterwards you can
+<<_verify_that_it_works, verify that it works>>.
 
 == Setup
 
 Several requirements should have already been installed in the xref:getting_started/installation.adoc[Installation guide]:
 
-* xref:commons-operator::index.adoc[Commons Operator]
-* xref:secret-operator::index.adoc[Secret Operator]
-* xref:hive::index.adoc[Hive Operator]
+* xref:commons-operator:index.adoc[Commons Operator]
+* xref:secret-operator:index.adoc[Secret Operator]
+* xref:hive:index.adoc[Hive Operator]
 * PostgreSQL
 * MinIO for S3
 
@@ -68,7 +70,8 @@ NAME                                 READY   AGE
 hive-postgres-s3-metastore-default   1/1     48s
 ----
 
-For further testing we recommend to use e.g. the python https://github.com/quintoandar/hive-metastore-client[hive-metastore-client] in order to e.g. create tables or connect a product like Trino via the xref:trino::index.adoc[Stackable Trino Operator].
+For further testing we recommend to use e.g. the python https://github.com/quintoandar/hive-metastore-client[hive-metastore-client]
+in order to e.g. create tables or connect a product like Trino via the xref:trino:index.adoc[Stackable Trino Operator].
 
 == What's next
 

docs/modules/hive/pages/getting_started/installation.adoc

@@ -1,23 +1,29 @@
 = Installation
 
-On this page you will install the Stackable Operator for Apache Hive and all required dependencies. For the installation of the dependencies and operators you can use Helm or stackablectl.
+On this page you will install the Stackable Operator for Apache Hive and all required dependencies. For the installation
+of the dependencies and operators you can use Helm or `stackablectl`.
 
-The stackablectl command line tool is the recommended way to interact with operators and dependencies. Follow the xref:stackablectl::installation.adoc[installation steps] for your platform if you choose to work with stackablectl.
+The `stackablectl` command line tool is the recommended way to interact with operators and dependencies. Follow the
+xref:management:stackablectl:installation.adoc[installation steps] for your platform if you choose to work with
+`stackablectl`.
 
 == Dependencies
 
-First you need to install MinIO and PostgreSQL instances for the Hive metastore. PostgreSQL is required as a database for Hive's metadata, and MinIO will be used as a data store, which the Hive metastore also needs access to.
+First you need to install MinIO and PostgreSQL instances for the Hive metastore. PostgreSQL is required as a database
+for Hive's metadata, and MinIO will be used as a data store, which the Hive metastore also needs access to.
 
 There are two ways to install the dependencies:
 
-1. Using xref:stackablectl::index.adoc[stackablectl]
-2. Using Helm
+. Using xref:management:stackablectl:index.adoc[stackablectl]
+. Using Helm
 
 WARNING: The dependency installations in this guide are only intended for testing and not suitable for production!
 
 === stackablectl
 
-stackablectl was designed to install Stackable components, but its xref:stackablectl::commands/stack.adoc[Stacks] feature can also be used to install arbitrary Helm Charts. You can install MinIO and PostgreSQL using the Stacks feature as follows, but a simpler method via Helm is shown <<Helm, below>>.
+`stackablectl` was designed to install Stackable components, but its xref:management:stackablectl:commands/stack.adoc[Stacks]
+feature can also be used to install arbitrary Helm Charts. You can install MinIO and PostgreSQL using the Stacks feature
+as follows, but a simpler method via Helm is shown <<Helm, below>>.
 
 [source,bash]
 ----
@@ -54,16 +60,17 @@ include::example$getting_started/release.yaml[]
 
 The release definition already references the required operators for this Getting Started guide.
 
-Now call stackablectl and reference those two files:
+Now call `stackablectl` and reference those two files:
 
 [source,bash]
 ----
 include::example$getting_started/getting_started.sh[tag=stackablectl-install-minio-postgres-stack]
 ----
 
-This will install MinIO and PostgreSQL as defined in the Stacks, as well as the Operators. You can now skip the <<Stackable Operators>> step that follows next.
+This will install MinIO and PostgreSQL as defined in the Stacks, as well as the Operators. You can now skip the
+<<Stackable Operators>> step that follows next.
 
-TIP: Consult the xref:stackablectl::quickstart.adoc[Quickstart] to learn more about how to use stackablectl.
+TIP: Consult the xref:management:stackablectl:quickstart.adoc[Quickstart] to learn more about how to use `stackablectl`.
 
 === Helm
 
@@ -89,8 +96,8 @@ After the dependencies are deployed, you can start to install the operators.
 
 There are 2 ways to run Stackable Operators:
 
-1. Using xref:stackablectl::index.adoc[stackablectl]
-2. Using Helm
+. Using xref:management:stackablectl:index.adoc[stackablectl]
+. Using Helm
 
 === stackablectl
 
@@ -126,7 +133,8 @@ Then install the Stackable operators:
 include::example$getting_started/getting_started.sh[tag=helm-install-operators]
 ----
 
-Helm will deploy the operators in a Kubernetes Deployment and apply the CRDs for the Apache Hive service (as well as the CRDs for the required operators). You are now ready to deploy the Apache Hive metastore in Kubernetes.
+Helm will deploy the operators in a Kubernetes Deployment and apply the CRDs for the Apache Hive service (as well as the
+CRDs for the required operators). You are now ready to deploy the Apache Hive metastore in Kubernetes.
 
 == What's next
 

docs/modules/hive/pages/index.adoc

@@ -2,49 +2,64 @@
 :description: The Stackable Operator for Apache Hive is a Kubernetes operator that can manage Apache Hive metastores. Learn about its features, resources, dependencies and demos, and see the list of supported Hive versions.
 :keywords: Stackable Operator, Hadoop, Apache Hive, Kubernetes, k8s, operator, engineer, big data, metadata, storage, query
 
-This is an operator for Kubernetes that can manage https://hive.apache.org[Apache Hive] metastores. 
-The Apache Hive metastore (HMS) was originally developed as part of Apache Hive. It stores information on the location of tables and partitions in file and blob storages such as xref:hdfs:index.adoc[Apache HDFS] and S3 and is now used by other tools besides Hive as well to access tables in files.
-This Operator does not support deploying Hive itself, but xref:trino:index.adoc[Trino] is recommended as an alternative query engine.
+This is an operator for Kubernetes that can manage https://hive.apache.org[Apache Hive] metastores.  The Apache Hive
+metastore (HMS) was originally developed as part of Apache Hive. It stores information on the location of tables and
+partitions in file and blob storages such as xref:hdfs:index.adoc[Apache HDFS] and S3 and is now used by other tools
+besides Hive as well to access tables in files. This Operator does not support deploying Hive itself, but
+xref:trino:index.adoc[Trino] is recommended as an alternative query engine.
 
 == Getting started
 
-Follow the xref:getting_started/index.adoc[Getting started guide] which will guide you through installing the Stackable Hive Operator and its dependencies. It walks you through setting up a Hive metastore and connecting it to a demo Postgres database and a Minio instance to store data in.
+Follow the xref:getting_started/index.adoc[Getting started guide] which will guide you through installing the Stackable
+Hive Operator and its dependencies. It walks you through setting up a Hive metastore and connecting it to a demo
+Postgres database and a Minio instance to store data in.
 
-Afterwards you can consult the xref:usage-guide/index.adoc[] to learn more about tailoring your Hive metastore configuration to your needs, or have a look at the <<demos, demos>> for some example setups with either xref:trino:index.adoc[Trino] or xref:spark-k8s:index.adoc[Spark].
+Afterwards you can consult the xref:usage-guide/index.adoc[] to learn more about tailoring your Hive metastore
+configuration to your needs, or have a look at the <<demos, demos>> for some example setups with either
+xref:trino:index.adoc[Trino] or xref:spark-k8s:index.adoc[Spark].
 
 == Operator model
 
-The Operator manages the _HiveCluster_ custom resource. The cluster implements a single `metastore` xref:home:concepts:roles-and-role-groups.adoc[role].
+The Operator manages the _HiveCluster_ custom resource. The cluster implements a single `metastore`
+xref:home:concepts:roles-and-role-groups.adoc[role].
 
 image::hive_overview.drawio.svg[A diagram depicting the Kubernetes resources created by the Stackable Operator for Apache Hive]
 
-For every role group the Operator creates a ConfigMap and StatefulSet which can have multiple replicas (Pods). Every role group is accessible through its own Service, and there is a Service for the whole cluster.
+For every role group the Operator creates a ConfigMap and StatefulSet which can have multiple replicas (Pods). Every
+role group is accessible through its own Service, and there is a Service for the whole cluster.
 
-The Operator creates a xref:concepts:service_discovery.adoc[service discovery ConfigMap] for the Hive metastore instance. The discovery ConfigMap contains information on how to connect to the HMS.
+The Operator creates a xref:concepts:service_discovery.adoc[service discovery ConfigMap] for the Hive metastore
+instance. The discovery ConfigMap contains information on how to connect to the HMS.
 
 == Dependencies
 
-The Stackable Operator for Apache Hive depends on the Stackable xref:commons-operator:index.adoc[commons] and xref:secret-operator:index.adoc[secret] operators.
+The Stackable Operator for Apache Hive depends on the Stackable xref:commons-operator:index.adoc[commons] and
+xref:secret-operator:index.adoc[secret] operators.
 
 == Required external component: An SQL database
 
-The Hive metastore requires a database to store metadata.
-Consult the xref:required-external-components.adoc[required external components page] for an overview of the supported databases and minimum supported versions.
+The Hive metastore requires a database to store metadata. Consult the xref:required-external-components.adoc[required
+external components page] for an overview of the supported databases and minimum supported versions.
 
 ==  [[demos]]Demos
 
 Three demos make use of the Hive metastore.
 
-The xref:stackablectl::demos/spark-k8s-anomaly-detection-taxi-data.adoc[] and xref:stackablectl::demos/trino-taxi-data.adoc[] use the HMS to store metadata information about taxi data. The first demo then analyzes the data using xref:spark-k8s:index.adoc[Apache Spark] and the second one using xref:trino:index.adoc[Trino].
+The xref:demos:spark-k8s-anomaly-detection-taxi-data.adoc[] and xref:demos:trino-taxi-data.adoc[] use the HMS to store
+metadata information about taxi data. The first demo then analyzes the data using xref:spark-k8s:index.adoc[Apache Spark]
+and the second one using xref:trino:index.adoc[Trino].
 
-The xref:stackablectl::demos/data-lakehouse-iceberg-trino-spark.adoc[] demo is the biggest demo available. It uses both Spark and Trino for analysis.
+The xref:demos:data-lakehouse-iceberg-trino-spark.adoc[] demo is the biggest demo available. It uses both Spark and
+Trino for analysis.
 
 == Why is the Hive query engine not supported?
 
-Only the metastore is supported, not Hive itself.
-There are several reasons why running Hive on Kubernetes may not be an optimal solution.
-The most obvious reason is that Hive requires YARN as an execution framework, and YARN assumes much of the same role as Kubernetes - i.e. assigning resources. 
-For this reason we provide xref:trino:index.adoc[Trino] as a query engine in the Stackable Data Platform instead of Hive. Trino still uses the Hive Metastore, hence the inclusion of this operator as well. Trino should offer all the capabilities Hive offers including a lot of additional functionality, such as connections to other data sources.
+Only the metastore is supported, not Hive itself. There are several reasons why running Hive on Kubernetes may not be an
+optimal solution. The most obvious reason is that Hive requires YARN as an execution framework, and YARN assumes much of
+the same role as Kubernetes - i.e. assigning resources. For this reason we provide xref:trino:index.adoc[Trino] as a
+query engine in the Stackable Data Platform instead of Hive. Trino still uses the Hive Metastore, hence the inclusion of
+this operator as well. Trino should offer all the capabilities Hive offers including a lot of additional functionality,
+such as connections to other data sources.
 
 Additionally, Tables in the HMS can also be accessed from xref:spark-k8s:index.adoc[Apache Spark].