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fix: Update demos and documentation #57

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f142863
update nifi-kafka-druid-water-level-data demo documentation and fix m…
xeniape Jun 24, 2024
74567ac
update stackablectl stacklet list
xeniape Jun 24, 2024
7af1f5a
update stackablectl stacklet list
xeniape Jun 24, 2024
ac98f4c
update nifi-kafka-druid-earthquake-data demo and adjustments for cons…
xeniape Jun 25, 2024
67a2939
update demo/stack resources, airflow-scheduled-job and hbase-hdfs-loa…
xeniape Jun 27, 2024
1876bad
update jupyterhub and logging demo documentation
xeniape Jun 27, 2024
bc0a848
update signal-processing demo and documentation
xeniape Jun 28, 2024
313de87
Update docs/modules/demos/pages/logging.adoc
xeniape Jul 3, 2024
ba11b63
Update docs/modules/demos/pages/jupyterhub-pyspark-hdfs-anomaly-detec…
xeniape Jul 3, 2024
5911d01
Update docs/modules/demos/pages/jupyterhub-pyspark-hdfs-anomaly-detec…
xeniape Jul 3, 2024
9e66a18
update spark-k8s-anomaly-detection-taxi-data demo documentation
xeniape Jul 4, 2024
8aa35ed
update trino-iceberg demo documentation
xeniape Jul 4, 2024
180ae78
Merge branch 'main' into fix/update-nifi-kafka-druid-documentation
xeniape Jul 4, 2024
249112c
update trino-taxi-data demo documentation
xeniape Jul 4, 2024
9d0297d
update data-lakehouse-iceberg-trino-spark demo and documentation
xeniape Jul 9, 2024
e63aeba
Merge branch 'main' into fix/update-nifi-kafka-druid-documentation
xeniape Jul 9, 2024
4267b72
Update docs/modules/demos/pages/trino-taxi-data.adoc
xeniape Jul 15, 2024
cf075ca
change doc ref
xeniape Jul 15, 2024
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change doc ref
xeniape Jul 15, 2024
ba9940d
change doc ref
xeniape Jul 15, 2024
7e8a5a7
update pvc resources for data-lakehouse-iceberg-trino-spark demo
xeniape Jul 16, 2024
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4 changes: 2 additions & 2 deletions demos/demos-v2.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -70,7 +70,7 @@ demos:
supportedNamespaces: ["default"]
resourceRequests:
cpu: 8700m
memory: 29746Mi
memory: 42034Mi
pvc: 75Gi # 30Gi for Kafka
nifi-kafka-druid-water-level-data:
description: Demo ingesting water level data into Kafka using NiFi, streaming it into Druid and creating a Superset dashboard
Expand All @@ -91,7 +91,7 @@ demos:
supportedNamespaces: ["default"]
resourceRequests:
cpu: 8900m
memory: 30042Mi
memory: 42330Mi
pvc: 75Gi # 30Gi for Kafka
spark-k8s-anomaly-detection-taxi-data:
description: Demo loading New York taxi data into an S3 bucket and carrying out an anomaly detection analysis on it
Expand Down
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Binary file added docs/modules/demos/images/logging/tenant.png
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4 changes: 2 additions & 2 deletions docs/modules/demos/pages/airflow-scheduled-job.adoc
Original file line number Diff line number Diff line change
Expand Up @@ -98,7 +98,7 @@ continuously:

image::airflow-scheduled-job/airflow_7.png[]

Click on the `run_every_minute` box in the centre of the page and then select `Log`:
Click on the `run_every_minute` box in the centre of the page and then select `Logs`:

[WARNING]
====
Expand All @@ -118,7 +118,7 @@ image::airflow-scheduled-job/airflow_10.png[]

Go back to DAG overview screen. The `sparkapp_dag` job has a scheduled entry of `None` and a last-execution time
(`2022-09-19, 07:36:55`). This allows a DAG to be executed exactly once, with neither schedule-based runs nor any
https://airflow.apache.org/docs/apache-airflow/stable/dag-run.html?highlight=backfill#backfill[backfill]. The DAG can
https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/dag-run.html#backfill[backfill]. The DAG can
always be triggered manually again via REST or from within the Webserver UI.

image::airflow-scheduled-job/airflow_11.png[]
Expand Down
54 changes: 26 additions & 28 deletions docs/modules/demos/pages/hbase-hdfs-load-cycling-data.adoc
Original file line number Diff line number Diff line change
Expand Up @@ -51,33 +51,31 @@ image::hbase-hdfs-load-cycling-data/overview.png[]

To list the installed Stackable services run the following command: `stackablectl stacklet list`

//TODO(Techassi): Update console output

[source,console]
----
$ stackablectl stacklet list
PRODUCT NAME NAMESPACE ENDPOINTS EXTRA INFOS

hbase hbase default regionserver 172.18.0.5:32282
ui http://172.18.0.5:31527
metrics 172.18.0.5:31081

hdfs hdfs default datanode-default-0-metrics 172.18.0.2:31441
datanode-default-0-data 172.18.0.2:32432
datanode-default-0-http http://172.18.0.2:30758
datanode-default-0-ipc 172.18.0.2:32323
journalnode-default-0-metrics 172.18.0.5:31123
journalnode-default-0-http http://172.18.0.5:30038
journalnode-default-0-https https://172.18.0.5:31996
journalnode-default-0-rpc 172.18.0.5:30080
namenode-default-0-metrics 172.18.0.2:32753
namenode-default-0-http http://172.18.0.2:32475
namenode-default-0-rpc 172.18.0.2:31639
namenode-default-1-metrics 172.18.0.4:32202
namenode-default-1-http http://172.18.0.4:31486
namenode-default-1-rpc 172.18.0.4:31874

zookeeper zookeeper default zk 172.18.0.4:32469

┌───────────┬───────────┬───────────┬──────────────────────────────────────────────────────────────┬─────────────────────────────────┐
│ PRODUCT ┆ NAME ┆ NAMESPACE ┆ ENDPOINTS ┆ CONDITIONS │
╞═══════════╪═══════════╪═══════════╪══════════════════════════════════════════════════════════════╪═════════════════════════════════╡
│ hbase ┆ hbase ┆ default ┆ regionserver 172.18.0.2:31521 ┆ Available, Reconciling, Running │
│ ┆ ┆ ┆ ui-http 172.18.0.2:32064 ┆ │
┆ ┆ metrics 172.18.0.2:31372 ┆ │
├╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ hdfs ┆ hdfs ┆ default datanode-default-0-listener-data 172.18.0.2:31990 ┆ Available, Reconciling, Running │
datanode-default-0-listener-http http://172.18.0.2:30659 ┆ │
┆ datanode-default-0-listener-ipc 172.18.0.2:30678 ┆ │
┆ datanode-default-0-listener-metrics 172.18.0.2:31531 ┆ │
┆ namenode-default-0-http http://172.18.0.2:32543 ┆ │
┆ namenode-default-0-metrics 172.18.0.2:30098 ┆ │
namenode-default-0-rpc 172.18.0.2:30915 ┆ │
namenode-default-1-http http://172.18.0.2:31333 ┆ │
namenode-default-1-metrics 172.18.0.2:30862 ┆ │
namenode-default-1-rpc 172.18.0.2:31440 ┆ │
├╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ zookeeper ┆ zookeeper ┆ default ┆ Available, Reconciling, Running │
└───────────┴───────────┴───────────┴──────────────────────────────────────────────────────────────┴─────────────────────────────────┘

----

include::partial$instance-hint.adoc[]
Expand Down Expand Up @@ -217,18 +215,18 @@ Below you will see the overview of your HDFS cluster.

image::hbase-hdfs-load-cycling-data/hdfs-overview.png[]

The UI will give you information on the datanodes via the datanodes tab.
The UI will give you information on the datanodes via the `Datanodes` tab.

image::hbase-hdfs-load-cycling-data/hdfs-datanode.png[]

You can also browse the filesystem via the Utilities menu.
You can also browse the file system by clicking on the `Utilities` tab and selecting `Browse the file system`.

image::hbase-hdfs-load-cycling-data/hdfs-data.png[]

The raw data from the distcp job can be found here.
Navigate in the file system to the folder `data` and then the `raw` folder. Here you can find the raw data from the distcp job.

image::hbase-hdfs-load-cycling-data/hdfs-data-raw.png[]

The structure of the Hfiles can be seen here.
Selecting the folder `data` and then `hfile` instead, gives you the structure of the Hfiles.

image::hbase-hdfs-load-cycling-data/hdfs-data-hfile.png[]
Original file line number Diff line number Diff line change
Expand Up @@ -87,7 +87,7 @@ There should be one parquet file containing taxi trip data from September 2020.

== JupyterHub

Have a look at the available Pods before logging in (operator pods are left out for clarity, you will see more Pods):
Have a look at the available Pods before logging in:

[source,console]
----
Expand Down Expand Up @@ -118,8 +118,8 @@ You should see the JupyterHub login page.

image::jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data/jupyter_hub_login.png[]

Log in with username `admin` and password `adminadmin`. There should appear a new pod called `jupyter-admin` (operator
pods are left out for clarity, you will see more Pods):
Log in with username `admin` and password `adminadmin`.
There should appear a new pod called `jupyter-admin`:

[source,console]
----
Expand All @@ -140,14 +140,14 @@ You should arrive at your workspace:

image::jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data/jupyter_hub_workspace.png[]

Now you can click on the `notebooks` folder on the left, open and run the contained file. Click on the double arrow (⏩️) to
execute the Python scripts.
Now you can double-click on the `notebook` folder on the left, open and run the contained file.
Click on the double arrow (⏩️) to execute the Python scripts.

image::jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data/jupyter_hub_run_notebook.png[]

You can also inspect the `hdfs` folder where the `core-site.xml` and `hdfs-site.xml` from
the discovery `ConfigMap` of the HDFS cluster are located.

image::jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data/jupyter_hub_run_notebook.png[]

[NOTE]
====
The image defined for the spark job must contain all dependencies needed for that job to run. For pyspark jobs, this
Expand Down
7 changes: 6 additions & 1 deletion docs/modules/demos/pages/logging.adoc
Original file line number Diff line number Diff line change
Expand Up @@ -86,7 +86,12 @@ Log in with the username `admin` and password `adminadmin`.

NOTE: On first login, you will be presented with some options. Feel free to bypass them to get to the logs.

Click _Discovery_ in the menu to view the recent logs. If you do not see anything, increase the search window to greater than _Last 15 minutes_.
Select the `Global` tenant to have access to the pre-configured `vector-*` index pattern.

image::logging/tenant.png[]

Click _Discover_ in the menu on the left to view the recent logs.
If you do not see anything, increase the search window to greater than _Last 15 minutes_.

image::logging/logs.png[]

Expand Down
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