[docs] redis-port -> port (#10937)

ci/long_running_distributed_tests/ray-project/cluster.yaml

@@ -80,7 +80,7 @@ setup_commands:
 head_start_ray_commands:
     - ray stop
     - export RAY_BACKEND_LOG_LEVEL=debug
-    - ray start --head --redis-port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml
+    - ray start --head --port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml
 
 # Command to start ray on worker nodes. You don't need to change this.
 worker_start_ray_commands:

ci/regression_test/rllib_regresssion_tests/ray-project/cluster.yaml

@@ -36,7 +36,7 @@ setup_commands:
 # Command to start ray on the head node. You don't need to change this.
 head_start_ray_commands:
     - source activate tensorflow_p36 && ray stop
-    - ulimit -n 65536; source activate tensorflow_p36 && OMP_NUM_THREADS=1 ray start --head --redis-port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml
+    - ulimit -n 65536; source activate tensorflow_p36 && OMP_NUM_THREADS=1 ray start --head --port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml
 
 # Command to start ray on worker nodes. You don't need to change this.
 worker_start_ray_commands:

ci/regression_test/rllib_stress_tests/ray-project/cluster.yaml

@@ -102,7 +102,7 @@ worker_setup_commands: []
 # Command to start ray on the head node. You don't need to change this.
 head_start_ray_commands:
     - source activate tensorflow_p36 && ray stop
-    - ulimit -n 65536; source activate tensorflow_p36 && OMP_NUM_THREADS=1 ray start --head --redis-port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml
+    - ulimit -n 65536; source activate tensorflow_p36 && OMP_NUM_THREADS=1 ray start --head --port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml
 
 # Command to start ray on worker nodes. You don't need to change this.
 worker_start_ray_commands:

ci/regression_test/stress_tests/ray-project/cluster.yaml

@@ -112,7 +112,7 @@ worker_setup_commands: []
 # Command to start ray on the head node. You don't need to change this.
 head_start_ray_commands:
     - ray stop
-    - ulimit -n 65536; ray start --head --num-redis-shards=5 --redis-port=6379 --autoscaling-config=~/ray_bootstrap_config.yaml
+    - ulimit -n 65536; ray start --head --port=6379 --autoscaling-config=~/ray_bootstrap_config.yaml
 
 # Command to start ray on worker nodes. You don't need to change this.
 worker_start_ray_commands:

deploy/ray-operator/config/samples/ray_v1_raycluster.complete.yaml

@@ -194,7 +194,7 @@ spec:
         key: value
 
       # Command to start ray
-      command: ray start --head --block --redis-port=6379 --node-ip-address=$MY_POD_IP --object-manager-port=12345 --node-manager-port=12346 --object-store-memory=100000000 --num-cpus=1
+      command: ray start --head --block --port=6379 --node-ip-address=$MY_POD_IP --object-manager-port=12345 --node-manager-port=12346 --object-store-memory=100000000 --num-cpus=1
 
       # use affinity to select nodes.Optional.
       # Refer to https://kubernetes.io/docs/concepts/configuration/assign-pod-node/#affinity-and-anti-affinity

deploy/ray-operator/config/samples/ray_v1_raycluster.heterogeneous.yaml

@@ -114,7 +114,7 @@ spec:
         raycluster.group.name: head-group
 
       # Command to start ray
-      command: ray start --head --block --redis-port=6379 --node-ip-address=$MY_POD_IP --object-manager-port=12345 --node-manager-port=12346 --object-store-memory=100000000 --num-cpus=1
+      command: ray start --head --block --port=6379 --node-ip-address=$MY_POD_IP --object-manager-port=12345 --node-manager-port=12346 --object-store-memory=100000000 --num-cpus=1
 
       # resource requirements
       # Refer to https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/

deploy/ray-operator/config/samples/ray_v1_raycluster.mini.yaml

@@ -56,7 +56,7 @@ spec:
         raycluster.group.name: head-group
 
       # Command to start ray
-      command: ray start --head --block --redis-port=6379 --node-ip-address=$MY_POD_IP --object-manager-port=12345 --node-manager-port=12346 --object-store-memory=100000000 --num-cpus=1
+      command: ray start --head --block --port=6379 --node-ip-address=$MY_POD_IP --object-manager-port=12345 --node-manager-port=12346 --object-store-memory=100000000 --num-cpus=1
 
       # resource requirements
       # Refer to https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/

doc/azure/azure-init.sh

@@ -19,7 +19,7 @@ NUM_GPUS=\`nvidia-smi -L | wc -l\`
 
 ray stop
 ulimit -n 65536
-ray start --head --redis-port=6379 --object-manager-port=8076 --num-gpus=\$NUM_GPUS --block --webui-host 0.0.0.0
+ray start --head -port=6379 --object-manager-port=8076 --num-gpus=\$NUM_GPUS --block --webui-host 0.0.0.0
 EOM
 
 cat > /home/"$USERNAME"/ray-worker.sh << EOM

doc/examples/lm/lm-cluster.yaml

@@ -117,7 +117,7 @@ worker_setup_commands: []
 head_start_ray_commands:
     - ray stop
     - ulimit -n 65536;
-        ray start --head --redis-port=6379
+        ray start --head --port=6379
         --object-manager-port=8076
         --autoscaling-config=~/ray_bootstrap_config.yaml
 

doc/kubernetes/ray-cluster.yaml

@@ -63,7 +63,7 @@ spec:
           imagePullPolicy: Always
           command: [ "/bin/bash", "-c", "--" ]
           args: 
-            - "ray start --head --node-ip-address=$MY_POD_IP --redis-port=6379 --redis-shard-ports=6380,6381 --num-cpus=$MY_CPU_REQUEST --object-manager-port=12345 --node-manager-port=12346 --block"
+            - "ray start --head --node-ip-address=$MY_POD_IP --port=6379 --redis-shard-ports=6380,6381 --num-cpus=$MY_CPU_REQUEST --object-manager-port=12345 --node-manager-port=12346 --block"
           ports:
             - containerPort: 6379 # Redis port.
             - containerPort: 6380 # Redis port.

doc/source/cluster/yarn.rst

@@ -114,7 +114,7 @@ and heap memory to roughly 200 MB. This is conservative and should be set accord
 
 .. code-block:: bash
 
-    ray start --head --redis-port=6379 --object-store-memory=200000000 --memory 200000000 --num-cpus=1
+    ray start --head --port=6379 --object-store-memory=200000000 --memory 200000000 --num-cpus=1
 
 Execute the user script containing the Ray program.
 

doc/yarn/ray-skein.yaml

@@ -28,7 +28,7 @@ services:
             # By default, we set object store memory and heap memory to roughly 200 MB. This is conservative
             # and should be set according to application needs.
             #
-            ray start --head --redis-port=6379 --object-store-memory=200000000 --memory 200000000 --num-cpus=1
+            ray start --head --port=6379 --object-store-memory=200000000 --memory 200000000 --num-cpus=1
 
             # This executes the user script.
             python example.py

python/ray/autoscaler/aws/development-example.yaml

@@ -111,7 +111,7 @@ worker_setup_commands: []
 # Command to start ray on the head node. You don't need to change this.
 head_start_ray_commands:
     - ray stop
-    - ulimit -n 65536; ray start --head --num-redis-shards=10 --port=6379 --autoscaling-config=~/ray_bootstrap_config.yaml
+    - ulimit -n 65536; ray start --head --port=6379 --autoscaling-config=~/ray_bootstrap_config.yaml
 
 # Command to start ray on worker nodes. You don't need to change this.
 worker_start_ray_commands:

python/ray/scripts/scripts.py

@@ -525,9 +525,8 @@ def start(node_ip_address, address, port, redis_password, redis_shard_ports,
             cli_logger.abort("`{}` should not be specified without `{}`.",
                              cf.bold("--port"), cf.bold("--head"))
 
-            raise Exception(
-                "If --head is not passed in, --port and --redis-port are not "
-                "allowed.")
+            raise Exception("If --head is not passed in, --port is not "
+                            "allowed.")
         if redis_shard_ports is not None:
             cli_logger.abort("`{}` should not be specified without `{}`.",
                              cf.bold("--redis-shard-ports"), cf.bold("--head"))

python/ray/util/sgd/tf/examples/tf-example-sgd.yaml

@@ -61,7 +61,7 @@ worker_setup_commands: []
 # # Command to start ray on the head node. You don't need to change this.
 head_start_ray_commands:
     - ray stop
-    - ray start --head --redis-port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml --object-store-memory=1000000000
+    - ray start --head --port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml --object-store-memory=1000000000
 
 # Command to start ray on worker nodes. You don't need to change this.
 worker_start_ray_commands:

python/ray/util/sgd/torch/examples/example-sgd.yaml

@@ -62,7 +62,7 @@ worker_setup_commands: []
 # # Command to start ray on the head node. You don't need to change this.
 head_start_ray_commands:
     - ray stop
-    - ray start --head --redis-port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml --object-store-memory=1000000000
+    - ray start --head --port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml --object-store-memory=1000000000
 
 # Command to start ray on worker nodes. You don't need to change this.
 worker_start_ray_commands: