バージョン: 3.8 (unsupported)

Getting Started with Helm Charts (ScalarDB Analytics with PostgreSQL)

This guide explains how to get started with ScalarDB Analytics with PostgreSQL by using a Helm Chart in a Kubernetes cluster as a test environment. In addition, the contents of this guide assume that you already have a Mac or Linux environment set up for testing. Although minikube is mentioned, the steps described should work in any Kubernetes cluster.

What you will create

You will deploy the following components in a Kubernetes cluster:

+-------------------------------------------------------------------------------------------------------------------------------------------+
| [Kubernetes cluster]                                                                                                                      |
|                                                                                                                                           |
|    [Pod]                                     [Pod]                                               [Pod]                                    |
|                                                                                                                                           |
|                                            +------------------------------------+                                                         |
|                                      +---> | ScalarDB Analytics with PostgreSQL | ---+         +-----------------------------+            |
|                                      |     +------------------------------------+    |   +---> |  MySQL ("customer" schema)  | <---+      |
|                                      |                                               |   |     +-----------------------------+     |      |
|  +-------------+      +---------+    |     +------------------------------------+    |   |                                         |      |
|  | OLAP client | ---> | Service | ---+---> | ScalarDB Analytics with PostgreSQL | ---+---+                                         +---+  |
|  +-------------+      +---------+    |     +------------------------------------+    |   |                                         |   |  |
|                                      |                                               |   |     +-----------------------------+     |   |  |
|                                      |     +------------------------------------+    |   +---> | PostgreSQL ("order" schema) | <---+   |  |
|                                      +---> | ScalarDB Analytics with PostgreSQL | ---+         +-----------------------------+         |  |
|                                            +------------------------------------+                                                      |  |
|                                                                                                                                        |  |
|  +-------------+                                                                                                                       |  |
|  | OLTP client | ---(Load sample data with a test OLTP workload)-----------------------------------------------------------------------+  |
|  +-------------+                                                                                                                          |
|                                                                                                                                           |
+-------------------------------------------------------------------------------------------------------------------------------------------+

Step 1. Start a Kubernetes cluster

First, you need to prepare a Kubernetes cluster. If you're using a minikube environment, please refer to the Getting Started with Scalar Helm Charts. If you have already started a Kubernetes cluster, you can skip this step.

Step 2. Start MySQL and PostgreSQL pods

ScalarDB including ScalarDB Analytics with PostgreSQL can use several types of database systems as a backend database. In this guide, you will use MySQL and PostgreSQL.

You can deploy MySQL and PostgreSQL on the Kubernetes cluster as follows:

Add the Bitnami helm repository.

helm repo add bitnami https://charts.bitnami.com/bitnami

Update the helm repository.
```
helm repo update bitnami
```

Deploy MySQL.

helm install mysql-scalardb bitnami/mysql \
  --set auth.rootPassword=mysql \
  --set primary.persistence.enabled=false

Deploy PostgreSQL.

helm install postgresql-scalardb bitnami/postgresql \
  --set auth.postgresPassword=postgres \
  --set primary.persistence.enabled=false

Check if the MySQL and PostgreSQL pods are running.

kubectl get pod

You should see the following output:

$ kubectl get pod
NAME                    READY   STATUS    RESTARTS   AGE
mysql-scalardb-0        1/1     Running   0          3m17s
postgresql-scalardb-0   1/1     Running   0          3m12s

Step 3. Create a working directory

Since you'll be creating some configuration files locally, create a working directory for those files.

mkdir -p ~/scalardb-analytics-postgresql-test/

Step 4. Set the versions of ScalarDB, ScalarDB Analytics with PostgreSQL, and the chart

Set the following three environment variables. If you want to use another version of ScalarDB and ScalarDB Analytics with PostgreSQL, be sure to set them to the versions that you want to use.

注記

You must use the same minor versions (for example, 3.10.x) of ScalarDB Analytics with PostgreSQL as ScalarDB, but you don't need to make the patch versions match. For example, you can use ScalarDB 3.10.1 and ScalarDB Analytics with PostgreSQL 3.10.3 together.

SCALARDB_VERSION=3.10.1

SCALARDB_ANALYTICS_WITH_POSTGRESQL_VERSION=3.10.3

CHART_VERSION=$(helm search repo scalar-labs/scalardb-analytics-postgresql -l | grep  -e ${SCALARDB_ANALYTICS_WITH_POSTGRESQL_VERSION} | awk '{print $2}' | sort --version-sort -r | head -n 1)

Step 5. Run OLTP transactions to load sample data to MySQL and PostgreSQL

Before deploying ScalarDB Analytics with PostgreSQL, run the OLTP transactions to create sample data.

Start an OLTP client pod in the Kubernetes cluster.

kubectl run oltp-client --image eclipse-temurin:8-jdk-jammy --env SCALARDB_VERSION=${SCALARDB_VERSION} -- sleep inf

Check if the OLTP client pod is running.

kubectl get pod oltp-client

You should see the following output:

$ kubectl get pod oltp-client
NAME          READY   STATUS    RESTARTS   AGE
oltp-client   1/1     Running   0          17s

Run bash in the OLTP client pod.
```
kubectl exec -it oltp-client -- bash
```
After this step, run each command in the OLTP client pod.
Install the git and curl commands in the OLTP client pod.
```
apt update && apt install -y curl git
```

Clone the ScalarDB samples repository.

git clone https://github.com/scalar-labs/scalardb-samples.git

Go to the directory scalardb-samples/multi-storage-transaction-sample/.

cd scalardb-samples/multi-storage-transaction-sample/

pwd

You should see the following output:

# pwd
/scalardb-samples/multi-storage-transaction-sample

Create a configuration file (database.properties) to access MySQL and PostgreSQL in the Kubernetes cluster.

cat << 'EOF' > database.properties
scalar.db.storage=multi-storage
scalar.db.multi_storage.storages=storage0,storage1

# Storage 0
scalar.db.multi_storage.storages.storage0.storage=jdbc
scalar.db.multi_storage.storages.storage0.contact_points=jdbc:mysql://mysql-scalardb.default.svc.cluster.local:3306/
scalar.db.multi_storage.storages.storage0.username=root
scalar.db.multi_storage.storages.storage0.password=mysql

# Storage 1
scalar.db.multi_storage.storages.storage1.storage=jdbc
scalar.db.multi_storage.storages.storage1.contact_points=jdbc:postgresql://postgresql-scalardb.default.svc.cluster.local:5432/postgres
scalar.db.multi_storage.storages.storage1.username=postgres
scalar.db.multi_storage.storages.storage1.password=postgres

scalar.db.multi_storage.namespace_mapping=customer:storage0,order:storage1
scalar.db.multi_storage.default_storage=storage1
EOF

Download Schema Loader from ScalarDB Releases.

curl -OL https://github.com/scalar-labs/scalardb/releases/download/v${SCALARDB_VERSION}/scalardb-schema-loader-${SCALARDB_VERSION}.jar

Run Schema Loader to create sample tables.

java -jar scalardb-schema-loader-${SCALARDB_VERSION}.jar --config database.properties --schema-file schema.json --coordinator

Load initial data for the sample workload.
```
./gradlew run --args="LoadInitialData"
```

Run the sample workload of OLTP transactions. Running these commands will create several order entries as sample data.

./gradlew run --args="PlaceOrder 1 1:3,2:2"

./gradlew run --args="PlaceOrder 1 5:1"

./gradlew run --args="PlaceOrder 2 3:1,4:1"

./gradlew run --args="PlaceOrder 2 2:1"

./gradlew run --args="PlaceOrder 3 1:1"

./gradlew run --args="PlaceOrder 3 2:1"

./gradlew run --args="PlaceOrder 3 3:1"

./gradlew run --args="PlaceOrder 3 5:1"

Exit from OLTP client.
```
exit
```

Step 6. Deploy ScalarDB Analytics with PostgreSQL

After creating sample data via ScalarDB in the backend databases, deploy ScalarDB Analytics with PostgreSQL.

Create a custom values file for ScalarDB Analytics with PostgreSQL (scalardb-analytics-postgresql-custom-values.yaml).

cat << 'EOF' > ~/scalardb-analytics-postgresql-test/scalardb-analytics-postgresql-custom-values.yaml
scalardbAnalyticsPostgreSQL:
  databaseProperties: |
    scalar.db.storage=multi-storage
    scalar.db.multi_storage.storages=storage0,storage1
    
    # Storage 0
    scalar.db.multi_storage.storages.storage0.storage=jdbc
    scalar.db.multi_storage.storages.storage0.contact_points=jdbc:mysql://mysql-scalardb.default.svc.cluster.local:3306/
    scalar.db.multi_storage.storages.storage0.username=root
    scalar.db.multi_storage.storages.storage0.password=mysql
    
    # Storage 1
    scalar.db.multi_storage.storages.storage1.storage=jdbc
    scalar.db.multi_storage.storages.storage1.contact_points=jdbc:postgresql://postgresql-scalardb.default.svc.cluster.local:5432/postgres
    scalar.db.multi_storage.storages.storage1.username=postgres
    scalar.db.multi_storage.storages.storage1.password=postgres
    
    scalar.db.multi_storage.namespace_mapping=customer:storage0,order:storage1
    scalar.db.multi_storage.default_storage=storage1
schemaImporter:
  namespaces:
    - customer
    - order
EOF

Create a secret resource to set a superuser password for PostgreSQL.

kubectl create secret generic scalardb-analytics-postgresql-superuser-password --from-literal=superuser-password=scalardb-analytics

Deploy ScalarDB Analytics with PostgreSQL.

helm install scalardb-analytics-postgresql scalar-labs/scalardb-analytics-postgresql -n default -f ~/scalardb-analytics-postgresql-test/scalardb-analytics-postgresql-custom-values.yaml --version ${CHART_VERSION}

Step 7. Run an OLAP client pod

To run some queries via ScalarDB Analytics with PostgreSQL, run an OLAP client pod.

Start an OLAP client pod in the Kubernetes cluster.

kubectl run olap-client --image postgres:latest -- sleep inf

Check if the OLAP client pod is running.

kubectl get pod olap-client

You should see the following output:

$ kubectl get pod olap-client
NAME          READY   STATUS    RESTARTS   AGE
olap-client   1/1     Running   0          10s

Step 8. Run sample queries via ScalarDB Analytics with PostgreSQL

After running the OLAP client pod, you can run some queries via ScalarDB Analytics with PostgreSQL.

Run bash in the OLAP client pod.
```
kubectl exec -it olap-client -- bash
```
After this step, run each command in the OLAP client pod.
Run the psql command to access ScalarDB Analytics with PostgreSQL.
```
psql -h scalardb-analytics-postgresql -p 5432 -U postgres -d scalardb
```
The password is scalardb-analytics.

Read sample data in the customer.customers table.

SELECT * FROM customer.customers;

You should see the following output:

 customer_id |     name      | credit_limit | credit_total
-------------+---------------+--------------+--------------
           1 | Yamada Taro   |        10000 |        10000
           2 | Yamada Hanako |        10000 |         9500
           3 | Suzuki Ichiro |        10000 |         8500
(3 rows)

Read sample data in the order.orders table.

SELECT * FROM "order".orders;

You should see the following output:

scalardb=# SELECT * FROM "order".orders;
 customer_id |   timestamp   |               order_id
-------------+---------------+--------------------------------------
           1 | 1700124015601 | 5ae2a41b-990d-4a16-9700-39355e29adf8
           1 | 1700124021273 | f3f23d93-3862-48be-8a57-8368b7c8689e
           2 | 1700124028182 | 696a895a-8998-4c3b-b112-4d5763bfcfd8
           2 | 1700124036158 | 9215d63a-a9a2-4471-a990-45897f091ca5
           3 | 1700124043744 | 9be70cd4-4f93-4753-9d89-68e250b2ac51
           3 | 1700124051162 | 4e8ce2d2-488c-40d6-aa52-d9ecabfc68a8
           3 | 1700124058096 | 658b6682-2819-41f2-91ee-2802a1f02857
           3 | 1700124071240 | 4e2f94f4-53ec-4570-af98-7c648d8ed80f
(8 rows)

Read sample data in the order.statements table.

SELECT * FROM "order".statements;

You should see the following output:

scalardb=# SELECT * FROM "order".statements;
               order_id               | item_id | count
--------------------------------------+---------+-------
 5ae2a41b-990d-4a16-9700-39355e29adf8 |       2 |     2
 5ae2a41b-990d-4a16-9700-39355e29adf8 |       1 |     3
 f3f23d93-3862-48be-8a57-8368b7c8689e |       5 |     1
 696a895a-8998-4c3b-b112-4d5763bfcfd8 |       4 |     1
 696a895a-8998-4c3b-b112-4d5763bfcfd8 |       3 |     1
 9215d63a-a9a2-4471-a990-45897f091ca5 |       2 |     1
 9be70cd4-4f93-4753-9d89-68e250b2ac51 |       1 |     1
 4e8ce2d2-488c-40d6-aa52-d9ecabfc68a8 |       2 |     1
 658b6682-2819-41f2-91ee-2802a1f02857 |       3 |     1
 4e2f94f4-53ec-4570-af98-7c648d8ed80f |       5 |     1
(10 rows)

Read sample data in the order.items table.

SELECT * FROM "order".items;

You should see the following output:

scalardb=# SELECT * FROM "order".items;
 item_id |  name  | price
---------+--------+-------
       5 | Melon  |  3000
       2 | Orange |  2000
       4 | Mango  |  5000
       1 | Apple  |  1000
       3 | Grape  |  2500
(5 rows)

Run the JOIN query. For example, you can see the credit remaining information of each user as follows.

SELECT * FROM (
    SELECT c.name, c.credit_limit - c.credit_total AS remaining, array_agg(i.name) OVER (PARTITION BY c.name) AS items
    FROM "order".orders o
    JOIN customer.customers c ON o.customer_id = c.customer_id
    JOIN "order".statements s ON o.order_id = s.order_id
    JOIN "order".items i ON s.item_id = i.item_id
) AS remaining_info GROUP BY name, remaining, items;

You should see the following output:

scalardb=# SELECT * FROM (
scalardb(#     SELECT c.name, c.credit_limit - c.credit_total AS remaining, array_agg(i.name) OVER (PARTITION BY c.name) AS items
scalardb(#     FROM "order".orders o
scalardb(#     JOIN customer.customers c ON o.customer_id = c.customer_id
scalardb(#     JOIN "order".statements s ON o.order_id = s.order_id
scalardb(#     JOIN "order".items i ON s.item_id = i.item_id
scalardb(# ) AS remaining_info GROUP BY name, remaining, items;
     name      | remaining |           items
---------------+-----------+----------------------------
 Suzuki Ichiro |      1500 | {Grape,Orange,Apple,Melon}
 Yamada Hanako |       500 | {Orange,Grape,Mango}
 Yamada Taro   |         0 | {Orange,Melon,Apple}
(3 rows)

Exit from the psql command.
```
\q
```
Exit from the OLAP client pod.
```
exit
```

Step 9. Delete all resources

After completing the ScalarDB Analytics with PostgreSQL tests on the Kubernetes cluster, remove all resources.

Uninstall MySQL, PostgreSQL, and ScalarDB Analytics with PostgreSQL.

helm uninstall mysql-scalardb postgresql-scalardb scalardb-analytics-postgresql

Remove the client pods.

kubectl delete pod oltp-client olap-client --grace-period 0

Remove the secret resource.

kubectl delete secrets scalardb-analytics-postgresql-superuser-password

Remove the working directory and sample files.

cd ~

rm -rf ~/scalardb-analytics-postgresql-test/

What you will create​

Step 1. Start a Kubernetes cluster​

Step 2. Start MySQL and PostgreSQL pods​

Step 3. Create a working directory​

Step 4. Set the versions of ScalarDB, ScalarDB Analytics with PostgreSQL, and the chart​

Step 5. Run OLTP transactions to load sample data to MySQL and PostgreSQL​

Step 6. Deploy ScalarDB Analytics with PostgreSQL​

Step 7. Run an OLAP client pod​

Step 8. Run sample queries via ScalarDB Analytics with PostgreSQL​

Step 9. Delete all resources​

What you will create

Step 1. Start a Kubernetes cluster

Step 2. Start MySQL and PostgreSQL pods

Step 3. Create a working directory

Step 4. Set the versions of ScalarDB, ScalarDB Analytics with PostgreSQL, and the chart

Step 5. Run OLTP transactions to load sample data to MySQL and PostgreSQL

Step 6. Deploy ScalarDB Analytics with PostgreSQL

Step 7. Run an OLAP client pod

Step 8. Run sample queries via ScalarDB Analytics with PostgreSQL

Step 9. Delete all resources