With SPARK_WORKER_CORES=1 and 2 workers the cluster has 2 total cores.
LiveDashboard holds both — batch jobs wait indefinitely. 4 cores per
worker gives 8 total, enough to run streaming + batch concurrently.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
local-path provisioner is RWO-only; attaching a single PVC to master, two
workers, history-server, and streaming pod on separate nodes causes
Multi-Attach errors. Each pod now gets its own ephemeral emptyDir for
/spark-events. Event logging confs removed from CronJobs and streaming
Deployment (logs are pod-local and do not persist across restarts).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
3.5.x has no official Docker Hub image. 4.0.3 is the oldest available
scala2.13 variant on Docker Hub.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Scheduler uses requests (not limits) for placement. Previous 1Gi requests
per pod caused Insufficient memory even with plenty of physical RAM.
New requests: master 256Mi, workers 256Mi, history-server 128Mi.
Limits unchanged. SPARK_WORKER_MEMORY reduced to 512m to match worker budget.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Bitnami Spark chart requires a Broadcom commercial license. Replace with
plain Deployments using apache/spark:3.5.4-scala2.13-java17-ubuntu
(Apache 2.0, same image used by the analytics jobs):
- spark-master: Deployment + ClusterIP Service (ports 7077/8080)
- spark-worker: Deployment, 2 replicas, connects to spark-master:7077
- spark-history-server: updated to apache/spark image
Ingress backend corrected to spark-master:8080.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Janis Eccarius