fix(spark): cap executor cores to prevent job starvation

Spark standalone gives executors all worker cores by default.
LiveDashboard was consuming all 8 cores (2 workers x 4 cores).
- streaming: spark.executor.cores=1 (uses 1 core total)
- batch jobs: spark.executor.cores=2 (uses 4 cores total, 2 per executor)
Leaves headroom for concurrent streaming + batch.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

spark-analytics/base/streaming.yaml

@@ -53,6 +53,8 @@ spec:
             - --conf
             - spark.executor.instances=1
             - --conf
+            - spark.executor.cores=1
+            - --conf
             - spark.executor.memory=512m
             - --conf
             - spark.driver.memory=512m