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https://github.com/dataoneorg/dataone-indexer

DataONE Indexer subsystem
https://github.com/dataoneorg/dataone-indexer

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DataONE Indexer subsystem

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README 

          
# DataONE Indexer



Also see [RELEASE-NOTES.md](./RELEASE-NOTES.md)



The DataONE Indexer is a system that processes index tasks created by other components. The DataONE

Indexer comprises three main subsystems, each defined by its own helm subsystem chart:



- **index-worker**: a subsystem implementing a Worker class to process index jobs in parallel

- **rabbitmq**: a deployment of the RabbitMQ queue management system

- **solr**: a deployment of the SOLR full text search system



```mermaid

flowchart TB

  subgraph "`**DataONE Indexer

  Helm Chart**`"

    A("`Index Worker

    *(1..n)*`")

    A -- sub chart --> C("`RabbitMQ

    *(1..n)*`")

    A -- sub chart --> D("`solr

    *(1..n)*`")

  end

```



Clients are expected to register index task messages to be processed in the RabbitMQ queue. Upon

startup, the RabbitMQ workers register themselves as handlers of the index task messages. As

messages enter the queue, RabbitMQ dispatches these to registered workers in parallel, and workers

in turn process each associated object and insert a new index entry into SOLR.



See [LICENSE.md](./LICENSE.md) for the details of distributing this software.



## Building Docker image



The image can be built with either `docker` or `nerdctl` depending on which container environment

you have installed. For example using Rancher Desktop configured to use `nerdctl`:



```shell

mvn clean package -DskipTests

nerdctl build -t dataone-index-worker:2.4.0 -f docker/Dockerfile --build-arg TAG=2.4.0 .

```



If you are building locally for Kubernetes on rancher-desktop, you'll need to set the  namespace

to `k8s.io` using a build command such as:



```shell

mvn clean package -DskipTests

nerdctl build -t dataone-index-worker:2.4.0 -f docker/Dockerfile --build-arg TAG=2.4.0 \

         --namespace k8s.io  .

```



## Publish the image to GHCR



For the built image to be deployable in a remote kubernetes cluster, it must first be published to

an image registry that is visible to Kubernetes. For example, we can make the published image

available via the GitHub Container Registry (ghcr.io) so that it can be pulled by

Kubernetes. For this to work, the image must be tagged with the ghcr.io URL, so it can be published.

Then the image can be pushed to the registry after logging in with a suitable GitHub PAT.



Note that, for the image to be associated with a particular GitHub repository, a metadata LABEL can

be added to the image that associates it when it is built - see this entry in the Dockerfile:



```dockerfile

LABEL org.opencontainers.image.source="https://github.com/dataoneorg/dataone-indexer"

```



Commands for pushing the built image (example assuming tag is `2.4.0`):



```shell

GITHUB_PAT="your-own-secret-GitHub-Personal-Access-Token-goes-here"

TAG=2.4.0



nerdctl tag dataone-index-worker:$TAG ghcr.io/dataoneorg/dataone-index-worker:$TAG

echo $GITHUB_PAT | nerdctl login ghcr.io -u DataONEorg --password-stdin

nerdctl push ghcr.io/dataoneorg/dataone-index-worker:$TAG

```



Once the image has been pushed, it may be private and will need to be made public and assigned to

the `dataone-indexer` repository if the LABEL wasn't set as described above.



## Publishing the Helm Chart



The helm chart may also be published to a helm repository for use by others as a top-level

application deployment or as a dependency sub-chart. For example, we can publish the chart

via the GitHub Container Registry (ghcr.io). For this to work, the chart must contain an annotation

to associate it with the correct repository - see this entry in [`Chart.yaml`](./helm/Chart.yaml):



```yaml

# OCI Annotations - see https://github.com/helm/helm/pull/11204

sources:

  - https://github.com/dataoneorg/dataone-indexer

```



The chart must then be packaged:



```shell

helm package ./helm

```



...which creates a zipped tar file named `dataone-indexer-{version}.tgz`, where `{version}` reflects

the chart `version` in [`Chart.yaml`](./helm/Chart.yaml). The chart can then be published to the

correct ghcr.io URL, after logging in with a suitable GitHub PAT:



(example assumes the chart version is 0.5.0)

```shell

GITHUB_PAT="your-own-secret-GitHub-Personal-Access-Token-goes-here"

TAG=2.4.0

helm push  dataone-indexer-0.5.0.tgz  oci://ghcr.io/dataoneorg/charts

```

NOTE the use of **charts** in the oci url, in order to distinguish helm charts from docker images.



## Deploying the application via Helm



Helm provides a simple mechanism to install all application dependencies and configure the

application in a single command. To deploy using helm to a release named `d1index` and also in a

namespace named `d1index`, and then view the deployed pods and services, use a sequence like:



```shell

kubectl create namespace d1index



# to use the local files

helm install -n d1index d1index ./helm



# or to pull the packaged chart with a specific release version (e.g. 1.2.0)...

helm install -n d1index d1index oci://ghcr.io/dataoneorg/charts/dataone-indexer --version 1.2.0



kubectl -n d1index get all

```



and to uninstall the helm release, use:



```shell

helm -n d1index uninstall d1index

```



Note that this helm chart also installs rabbitmq and solr, which can be partially configured

through the values.yaml file in the parent chart through exported child properties.



> [!IMPORTANT]

> Make sure the RabbitMQ queue is empty, before upgrading or installing a new chart version for the

> first time, because each new chart version will create a new PV/PVC where the queue is stored.

> This can be overridden by setting .Values.rabbitmq.nameOverride to the same name as the previous

> version, but this is NOT recommended, since the RabbitMQ installation then becomes an upgrade

> instead of a fresh install, and may require some manual intervention.



### Authentication Notes



#### DataONE Authentication Token



In order to access and index private datasets on a Metacat instance, the dataone-indexer needs an

authentication token, which may be obtained from DataONE administrators (see the [Metacat Helm 

README](https://github.com/NCEAS/metacat/blob/develop/helm/README.md#setting-up-a-token-and-optional-ca-certificate-for-indexer-access)).

Upon startup, the indexer expects to find a Kubernetes Secret named:

`{{ .Release.Name }}-indexer-token`, which contains the auth token associated with the key 

`DataONEauthToken`. The indexer can operate without this Secret, but will only be able to index 

public-readable datasets.



#### RabbitMQ



The rabbitmq service runs under the username and password that are set via values.yaml



```yaml

rabbitmq:

  auth:

    username: rmq

    existingPasswordSecret: ""      ## (must contain key: `rabbitmq-password`)

```



...where `existingPasswordSecret` is the name of a Kubernetes secret that contains the password,

identified by a key named `rabbitmq-password`. 



> **NOTE:** it appears that this information is cached

on a PersistentVolumeClaim that is created automatically by rabbitmq. If the credentials are changed

in `values.yaml` and/or the secret, therefore, authentication will fail because they will conflict

with the cached values in the PVC. If you are just testing, the problem can be resolved by deleting

the PVC. In production, the PVC would also be used for maintaining durable queues, and so it may not

be reasonable to delete the PVC. You can get the name and identifiers of the PVCs with

`kubectl -n d1index get pvc`.



## Running the IndexWorker in the docker container



The docker image assumes that the deployment configuration file exists to configure endpoint

addresses and credentials. To run the indexer, ensure that the`DATAONE_INDEXER_CONFIG` is set in the

environment and contains the absolute path to the configuration file for the indexer. This path must

be accessible in the container, so you will likely want to mount a volume to provide the edited

properties file. You can then run it using a command like:



```shell

nerdctl run -it \

    -e DATAONE_INDEXER_CONFIG=/var/lib/dataone-indexer/dataone-indexer.properties \

    -v `pwd`/helm/config/dataone-indexer.properties:/var/lib/dataone-indexer/dataone-indexer.properties \

    dataone-index-worker:2.4.0

```



## A Note on SOLR Authentication



The helm installation does not currently configure solr with authentication enabled, since the

service is not exposed outside the Kubernetes cluster. Mentions of logins in the following sections

can therefore be ignored. However, this should be changed to use authentication if connecting to a

solr instance outside the cluster.



## Checking if SOLR is configured



Logging in using the SOLR_AUTHENTICATION_OPTS and SOLR_AUTH_TYPE env variables (if applicable)

allows the `solr` command to be executed to check the server status:



```shell

$ export SOLR_AUTH_TYPE=basic

$ export SOLR_AUTHENTICATION_OPTS="-Dbasicauth=${SOLR_ADMIN_USERNAME}:${SOLR_ADMIN_PASSWORD}"

$ solr status -z ${SOLR_ZK_HOSTS} -c ${SOLR_COLLECTION}



Found 1 Solr nodes:



Solr process 8 running on port 8983

{

  "solr_home":"/opt/bitnami/solr/server/solr",

  "version":"9.0.0 a4eb7aa123dc53f8dac74d80b66a490f2d6b4a26 - janhoy - 2022-05-05 01:00:08",

  "startTime":"2022-10-11T07:08:50.155Z",

  "uptime":"0 days, 0 hours, 21 minutes, 52 seconds",

  "memory":"70.9 MB (%13.8) of 512 MB",

  "cloud":{

    "ZooKeeper":"d1index-zookeeper:2181/solr",

    "liveNodes":"3",

    "collections":"1"}}

```



# SOLR Dashboard



Once the SOLR server is up and running, connect to the SOLR Dashboard by creating a kube proxy, and

then browse to the local address:



```shell

k8 port-forward -n d1index service/d1index-solr 8983:8983 & echo "Solr URL: 127.0.0.1:8983/solr/"

```



You'll need to log in with the helm-configured SOLR admin user and password, if applicable.



Once the proxy is set up, you can also run API calls from the [ConfigSet API](https://solr.apache.org/guide/6_6/configsets-api.html) and

[Collections API](https://solr.apache.org/guide/6_6/collections-api.html).



```shell

curl -u ${SOLR_ADMIN_USERNAME}:${SOLR_ADMIN_PASSWORD} http://localhost:8983/solr/admin/configs?action=CREATE\&name=dataone-index --header "Content-Type:text/xml" -X POST -d @dataone-index.zip

{

  "responseHeader":{

    "status":0,

    "QTime":5974}}

curl -u ${SOLR_ADMIN_USERNAME}:${SOLR_ADMIN_PASSWORD} http://localhost:8983/solr/admin/configs?action=list

curl -u ${SOLR_ADMIN_USERNAME}:${SOLR_ADMIN_PASSWORD} http://localhost:8983/solr/admin/collections?action=list

```



### Admin tools for rabbitmq



Once rabbitmq is configured, the web console can be accessed by port-forwarding.



```shell

k8 -n jones port-forward pod/d1index-rabbitmq-0 15672:15672 &

```



then login to the Rabbitmq web console: http://localhost:15672



You can also download a copy of `rabbitmqadmin` from http://localhost:15672/cli/rabbitmqadmin,

and the `rabbitmqadmin` command can be used to interact with the server. First, you need to set up a

config file for `rabbitmqadmin` that provides some default values:



```shell

$ cat rmq.conf

[default]

hostname = d1index-rabbitmq-headless

port = 15672

username = rmq

password = your-client-pw-here

declare_vhost = / # Used as default for declare / delete only

vhost = /         # Used as default for declare / delete / list

```



- List exchanges and queues

    - `rabbitmqadmin -c rmq.conf -N default -U rmq -p $RMQPW list exchanges --vhost=/`

    - `rabbitmqadmin -c rmq.conf -N default -U rmq -p $RMQPW list queues --vhost=/`

- Declare exchanges, queues, and bindings

    - `rabbitmqadmin -c rmq.conf -N default declare exchange name=testexchange type=direct -U rmq -p $RMQPW --vhost=/`

    - `rabbitmqadmin -c rmq.conf -N default declare queue name=testqueue type=direct -U rmq -p $RMQPW --vhost=/`

    - `rabbitmqadmin -c rmq.conf -N default -U rmq -p $RMQPW declare binding source=testexchange destination=testqueue routing_key=testqueue --vhost=/`

- Publish a bunch of messages to a queue

```

for n in $(seq 1 30); do echo $n; rabbitmqadmin -c rmq.conf -N default -U rmq -p $RMQPW publish exchange=testexchange routing_key=testqueue payload="Message: ${n}" --vhost=/; done

```



## Switching the Storage System

The Dataone Indexer can be configured to use different storage systems by setting the environmental

variable `DATAONE_INDEXER_OBJECT_MANAGER_CLASS_NAME`.

By default, this variable is not set, and the indexer uses

`org.dataone.cn.indexer.object.hashstore.HashStoreObjManager`, which enables support for Hashstore.

To use the legacy storage system instead, set the variable to

`org.dataone.cn.indexer.object.legacystore.LegacyStoreObjManager`.



## History



This is a refactored version of the original DataONE [d1_cn_index_processor](https://github.com/DataONEorg/d1_cn_index_processor) that runs

completely independently of other DataONE Coordinating Node services. It is intended to be deployed

in a Kubernetes cluster environment, but is written such that it can also be deployed in other

environments as needed.