Play with the SAP HANA database on Google Kubernetes cluster

Use the credentials provided by one of the experts at the booth at Google Next ’18 to log into the Google Cloud Platform console.

Once there, use the menu on the top left corner to navigate a new Kubernetes cluster from the Kubernetes Engine menu.

Click Create cluster.

Fill in the name, choose version 1.9.6 and click Customize.

Set the CPU to 2 and memory to 13. Choose Ubuntu as the operating system and set the size of the cluster to 1.

Scroll down and click Create.

The setup will take some time. Meanwhile, here is some information about what is SAP HANA, express edition to make waiting easier.

Once the cluster has finished deploying, click Connect.

Use Run in Cloud Shell to connect from the web console.

This will open a gcloud console with a command ready to connect to the cluster in your project and selected zone. Hit enter to execute the command.

Go back to the gcloud console for your cluster.

Create a secret to fetch the Docker image using the command below. Copy and paste the command into the console and press enter.

kubectl create secret docker-registry docker-secret --docker-server=https://index.docker.io/v1/ --docker-username=gnext18 --docker-password=SAP@Google --docker-email=hrocks@gmail.com

From the console, use the following commands to create a new file and open the web text editor:

touch hxe.yaml
edit hxe.yaml

Confirm opening an editor:

This will open an online editor where you will paste the contents of the file below.

kind: ConfigMap
apiVersion: v1
metadata:
  creationTimestamp: 2018-01-18T19:14:38Z
  name: hxe-pass
data:
  password.json: |+
    {"master_password" : "HXEHana1"}
---
kind: PersistentVolume
apiVersion: v1
metadata:
  name: persistent-vol-hxe
  labels:
    type: local
spec:
  storageClassName: manual
  capacity:
    storage: 150Gi
  accessModes:
    - ReadWriteOnce
  hostPath:
    path: "/data/hxe_pv"
---
kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: hxe-pvc
spec:
  storageClassName: manual
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
      storage: 50Gi
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: hxe
  labels:
    name: hxe
spec:
  selector:
    matchLabels:
      run: hxe
      app: hxe
      role: master
      tier: backend
  replicas: 1
  template:
    metadata:
      labels:
        run: hxe
        app: hxe
        role: master
        tier: backend
    spec:
      initContainers:
        - name: install
          image: busybox
          command: [ 'sh', '-c', 'chown 12000:79 /hana/mounts' ]
          volumeMounts:
            - name: hxe-data
              mountPath: /hana/mounts
      volumes:
        - name: hxe-data
          persistentVolumeClaim:
             claimName: hxe-pvc
        - name: hxe-config
          configMap:
             name: hxe-pass
      imagePullSecrets:
      - name: docker-secret
      containers:
      - name: hxe-container
        image: "store/saplabs/hanaexpress:2.00.030.00.20180403.2"
        ports:
          - containerPort: 39013
            name: port1
          - containerPort: 39015
            name: port2
          - containerPort: 39017
            name: port3
          - containerPort: 8090
            name: port4
          - containerPort: 39041
            name: port5
          - containerPort: 59013
            name: port6
        args: [ "--agree-to-sap-license", "--dont-check-system", "--passwords-url", "file:///hana/hxeconfig/password.json" ]
        volumeMounts:
          - name: hxe-data
            mountPath: /hana/mounts
          - name: hxe-config
            mountPath: /hana/hxeconfig
      - name: sqlpad-container
        image: "sqlpad/sqlpad"
        ports:
        - containerPort: 3000

---
apiVersion: v1
kind: Service
metadata:
  name: hxe-connect
  labels:
    app: hxe
spec:
  type: LoadBalancer
  ports:
  - port: 39013
    targetPort: 39013
    name: port1
  - port: 39015
    targetPort: 39015
    name: port2
  - port: 39017
    targetPort: 39017
    name: port3
  - port: 39041
    targetPort: 39041
    name: port5
  selector:
    app: hxe
---
apiVersion: v1
kind: Service
metadata:
  name: sqlpad
  labels:
    app: hxe
spec:
  type: LoadBalancer
  ports:
  - port: 3000
    targetPort: 3000
    protocol: TCP
    name: sqlpad
  selector:
    app: hxe

The file will be automatically saved to your home directory (/home/YOUR_GOOGLE_ID).

Use the following command to deploy the image on your pods and check deployment:

kubectl create -f hxe.yaml
kubectl describe pods

Initially, you will probably see a message stating that the image is being pulled. Repeat the command a couple of minutes later until you see the container is started:

Use the following command to check the name of the pod. Make sure the status is Running and 2/2.

kubectl get pods

Use the name of the pod to replace it in the following command

kubectl exec -it <<pod-name>> bash

For example:

Use the following SQL commands to connect to the database and enable document store for later user

hdbsql -i 90 -d systemdb -u SYSTEM -p HXEHana1

Paste the following command into the SQL prompt

alter database HXE add 'docstore';

Use quit to exit the SQL command line and exit

Get the external IP addresses from the SQLPAD service

kubectl get services

Open a new tab, and use the IP address and port 3000 to connect to SQLPAD. Click on Sign in to create an administration account

Fill in the details and create the account and sign up

Sign in using your credentials and use the Connections option on the top right corner to connect to your database

Use the external IP address from the hxe-connect service this time

Click on New connection and fill the details as below

Click New Query

Paste the following commands in SQLPAD. Execute them one by one by selecting them and pressing Run.

create collection quotes;


--Create a collection for document store and insert JSON values

insert into quotes values ( { "FROM" : 'HOMER',   "QUOTE" :  'I want to share something with you: The three little sentences that will get you through life. Number 1: Cover for me. Number 2: Oh, good idea, Boss! Number 3: It wai like that when I got here.', "MOES_BAR" : 'Point(  -86.880306 36.508361 )', "QUOTE_ID" : 1  });
insert into quotes values ( { "FROM" : 'HOMER',   "QUOTE" :  'Wait a minute. Bart''s teacher is named Krabappel? Oh, I''ve been calling her Crandall. Why did not anyone tell me? Ohhh, I have been making an idiot out of myself!', "QUOTE_ID" : 2, "MOES_BAR" : 'Point( -87.182708 37.213414 )' });
insert into quotes values ( { "FROM" : 'HOMER',   "QUOTE" :  'Oh no! What have I done? I smashed open my little boy''s piggy bank, and for what? A few measly cents, not even enough to buy one beer. Weit a minute, lemme count and make sure…not even close.', "MOES_BAR" : 'Point( -122.400690 37.784366 )', "QUOTE_ID" : 3 });

--Create a columnar table with a text fuzzy search index
create column table quote_analysis
(
	id integer,
	homer_quote text FAST PREPROCESS ON FUZZY SEARCH INDEX ON,
	lon_lat nvarchar(200)

);


-- Copy the quotes form the JSON store to the relational table
insert into quote_analysis
with doc_store as (select quote_id, quote from quotes)
select doc_store.quote_id as id, doc_store.quote as homer_quote, 'Point( -122.676366 45.535889 )'
from doc_store;


--Find out the lowest similarity with word "wait". Take note of the first ID
select  id, score() as similarity , lon_lat, TO_VARCHAR(HOMER_QUOTE)
from quote_analysis
where contains(HOMER_QUOTE, 'wait', fuzzy(0.5,'textsearch=compare'))
order by similarity asc

--Do you want a prize? Fill in the ID in the WHERE clause below with the first result in the previous query
-- to calculate the distance in kilometers between two points using the geospatial engine
-- Share the result with any of the experts, they will give you something to cope with the distance
with doc_store as (select quote_id, moes_bar from quotes)
select st_geomFromText( quote_analysis.lon_lat, 4326).st_distance(st_geomFromtext( doc_store.moes_bar, 4326), 'meter') / 1000 as DISTANCE_KM
from doc_store
inner join quote_analysis on doc_store.quote_id = <<Fill in with the ID of the lowest similarity score>>;

Congratulations!
You have completed this tutorial. Visit developers.sap.com to get your free deployment of SAP HANA, express edition and learn from hundreds of available tutorials.