fix(spark): lower memory requests to fix scheduling on resource-constrained nodes

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>

spark-cluster/base/master.yaml

@@ -29,8 +29,8 @@ spec:
               containerPort: 8080
           resources:
             requests:
-              cpu: 500m
-              memory: 1Gi
+              cpu: 200m
+              memory: 256Mi
             limits:
               cpu: "1"
               memory: 2Gi