diff --git a/Cargo.lock b/Cargo.lock
index 279cabe56c5d7..0738408abeba5 100644
--- a/Cargo.lock
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MV","editable":true,"error":false,"fieldConfig":{"defaults":{"color":{"mode":"palette-classic"},"custom":{"axisLabel":"","axisPlacement":"auto","barAlignment":0,"drawStyle":"line","fillOpacity":10,"gradientMode":"none","hideFrom":{"legend":false,"tooltip":false,"viz":false},"lineInterpolation":"linear","lineWidth":1,"pointSize":5,"scaleDistribution":{"log":2,"type":"linear"},"showPoints":"auto","spanNulls":false,"stacking":{},"thresholdsStyle":{"mode":"off"}},"mappings":[],"thresholds":{"mode":"absolute","steps":[]},"unit":"rows/s"},"overrides":[]},"gridPos":{"h":8,"w":12,"x":0,"y":8},"height":null,"hideTimeOverride":false,"id":38,"interval":"1s","links":[],"maxDataPoints":1000,"maxPerRow":null,"minSpan":null,"options":{"legend":{"calcs":["mean"],"displayMode":"table","placement":"right"},"tooltip":{"mode":"single"}},"repeat":null,"repeatDirection":null,"span":null,"targets":[{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"rate(stream_backfill_snapshot_read_row_count[$__rate_interval])","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"Read Snapshot - table_id={{table_id}} actor={{actor_id}} @ {{instance}}","metric":"","refId":"","step":10,"target":""},{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"rate(stream_backfill_upstream_output_row_count[$__rate_interval])","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"Upstream - table_id={{table_id}} actor={{actor_id}} @ {{instance}}","metric":"","refId":"","step":10,"target":""}],"timeFrom":null,"timeShift":null,"title":"Backfill Throughput(rows)","transformations":[],"transparent":false,"type":"timeseries"},{"cacheTimeout":null,"datasource":null,"description":"We first record the total blocking duration(ns) of output buffer of each actor. It shows how much time it takes an actor to process a message, i.e. a barrier, a watermark or rows of data, on average. Then we divide this duration by 1 second and show it as a percentage.","editable":true,"error":false,"fieldConfig":{"defaults":{"color":{"mode":"palette-classic"},"custom":{"axisLabel":"","axisPlacement":"auto","barAlignment":0,"drawStyle":"line","fillOpacity":10,"gradientMode":"none","hideFrom":{"legend":false,"tooltip":false,"viz":false},"lineInterpolation":"linear","lineWidth":1,"pointSize":5,"scaleDistribution":{"log":2,"type":"linear"},"showPoints":"auto","spanNulls":false,"stacking":{},"thresholdsStyle":{"mode":"off"}},"mappings":[],"thresholds":{"mode":"absolute","steps":[]},"unit":"percentunit"},"overrides":[]},"gridPos":{"h":8,"w":12,"x":12,"y":8},"height":null,"hideTimeOverride":false,"id":39,"interval":"1s","links":[],"maxDataPoints":1000,"maxPerRow":null,"minSpan":null,"options":{"legend":{"calcs":["mean"],"displayMode":"table","placement":"right"},"tooltip":{"mode":"single"}},"repeat":null,"repeatDirection":null,"span":null,"targets":[{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"rate(stream_actor_output_buffer_blocking_duration_ns[$__rate_interval]) / 1000000000","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"{{actor_id}}","metric":"","refId":"","step":10,"target":""}],"timeFrom":null,"timeShift":null,"title":"Actor Backpressure","transformations":[],"transparent":false,"type":"timeseries"}],"repeat":null,"repeatDirection":null,"span":null,"targets":[],"timeFrom":null,"timeShift":null,"title":"Streaming","transformations":[],"transparent":false,"type":"row"},{"cacheTimeout":null,"collapsed":true,"datasource":null,"description":null,"editable":true,"error":false,"fieldConfig":{"defaults":{"thresholds":{"mode":"absolute","steps":[]}}},"gridPos":{"h":1,"w":24,"x":0,"y":47},"height":null,"hideTimeOverride":false,"id":40,"interval":null,"links":[],"maxDataPoints":100,"maxPerRow":null,"minSpan":null,"panels":[{"cacheTimeout":null,"datasource":null,"description":"","editable":true,"error":false,"fieldConfig":{"defaults":{"color":{"mode":"palette-classic"},"custom":{"axisLabel":"","axisPlacement":"auto","barAlignment":0,"drawStyle":"line","fillOpacity":10,"gradientMode":"none","hideFrom":{"legend":false,"tooltip":false,"viz":false},"lineInterpolation":"linear","lineWidth":1,"pointSize":5,"scaleDistribution":{"log":2,"type":"linear"},"showPoints":"auto","spanNulls":false,"stacking":{},"thresholdsStyle":{"mode":"off"}},"mappings":[],"thresholds":{"mode":"absolute","steps":[]},"unit":""},"overrides":[]},"gridPos":{"h":8,"w":12,"x":0,"y":0},"height":null,"hideTimeOverride":false,"id":41,"interval":"1s","links":[],"maxDataPoints":1000,"maxPerRow":null,"minSpan":null,"options":{"legend":{"calcs":["last"],"displayMode":"table","placement":"right"},"tooltip":{"mode":"single"}},"repeat":null,"repeatDirection":null,"span":null,"targets":[{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"distributed_running_query_num","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"The number of running query in distributed execution mode","metric":"","refId":"","step":10,"target":""}],"timeFrom":null,"timeShift":null,"title":"Running query in distributed execution mode","transformations":[],"transparent":false,"type":"timeseries"},{"cacheTimeout":null,"datasource":null,"description":"","editable":true,"error":false,"fieldConfig":{"defaults":{"color":{"mode":"palette-classic"},"custom":{"axisLabel":"","axisPlacement":"auto","barAlignment":0,"drawStyle":"line","fillOpacity":10,"gradientMode":"none","hideFrom":{"legend":false,"tooltip":false,"viz":false},"lineInterpolation":"linear","lineWidth":1,"pointSize":5,"scaleDistribution":{"log":2,"type":"linear"},"showPoints":"auto","spanNulls":false,"stacking":{},"thresholdsStyle":{"mode":"off"}},"mappings":[],"thresholds":{"mode":"absolute","steps":[]},"unit":""},"overrides":[]},"gridPos":{"h":8,"w":12,"x":12,"y":0},"height":null,"hideTimeOverride":false,"id":42,"interval":"1s","links":[],"maxDataPoints":1000,"maxPerRow":null,"minSpan":null,"options":{"legend":{"calcs":["last"],"displayMode":"table","placement":"right"},"tooltip":{"mode":"single"}},"repeat":null,"repeatDirection":null,"span":null,"targets":[{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"distributed_rejected_query_counter","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"The number of rejected query in distributed execution mode","metric":"","refId":"","step":10,"target":""}],"timeFrom":null,"timeShift":null,"title":"Rejected query in distributed execution 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number of completed query in distributed execution mode","metric":"","refId":"","step":10,"target":""}],"timeFrom":null,"timeShift":null,"title":"Completed query in distributed execution 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sum(rate(distributed_query_latency_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p50 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""},{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"histogram_quantile(0.9, sum(rate(distributed_query_latency_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p90 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""},{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"histogram_quantile(0.95, sum(rate(distributed_query_latency_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p99 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""}],"timeFrom":null,"timeShift":null,"title":"Query Latency in Distributed Execution 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sum(rate(frontend_latency_local_execution_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p50 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""},{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"histogram_quantile(0.9, sum(rate(frontend_latency_local_execution_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p90 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""},{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"histogram_quantile(0.95, sum(rate(frontend_latency_local_execution_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p99 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""}],"timeFrom":null,"timeShift":null,"title":"Query Latency in Local Execution Mode","transformations":[],"transparent":false,"type":"timeseries"}],"repeat":null,"repeatDirection":null,"span":null,"targets":[],"timeFrom":null,"timeShift":null,"title":"Batch","transformations":[],"transparent":false,"type":"row"}],"refresh":"10s","rows":[],"schemaVersion":12,"sharedCrosshair":true,"style":"dark","tags":["risingwave"],"templating":{"list":[]},"time":{"from":"now-30m","to":"now"},"timepicker":{"hidden":false,"refresh_intervals":["5s","10s","30s","1m","5m","15m","30m","1h","2h","1d"],"time_options":["5m","15m","1h","6h","12h","24h","2d","7d","30d"]},"timezone":"browser","title":"risingwave_dashboard","uid":"Fcy3uV1nz","version":0}
diff --git a/grafana/common.py b/grafana/common.py
index c799287704d51..d2b252624a027 100644
--- a/grafana/common.py
+++ b/grafana/common.py
@@ -91,6 +91,12 @@ def next_one_third_width_graph(self):
 
 class Panels:
 
+    common_options = {
+        "fillOpacity": 10,
+        "interval": "1s",
+        "maxDataPoints": 1000,
+    }
+
     def __init__(self, datasource):
         self.layout = Layout()
         self.datasource = datasource
@@ -129,7 +135,7 @@ def timeseries(self, title, description, targets):
             description=description,
             targets=targets,
             gridPos=gridPos,
-            fillOpacity=10,
+            **self.common_options,
         )
 
     def timeseries_count(self,
@@ -143,10 +149,10 @@ def timeseries_count(self,
             description=description,
             targets=targets,
             gridPos=gridPos,
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_percentage(self,
@@ -162,10 +168,10 @@ def timeseries_percentage(self,
             targets=targets,
             gridPos=gridPos,
             unit="percentunit",
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_latency(self,
@@ -180,10 +186,10 @@ def timeseries_latency(self,
             targets=targets,
             gridPos=gridPos,
             unit="s",
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_actor_latency(self,
@@ -198,10 +204,10 @@ def timeseries_actor_latency(self,
             targets=targets,
             gridPos=gridPos,
             unit="s",
-            fillOpacity=0,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_actor_latency_small(self,
@@ -216,10 +222,10 @@ def timeseries_actor_latency_small(self,
             targets=targets,
             gridPos=gridPos,
             unit="s",
-            fillOpacity=0,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_query_per_sec(self,
@@ -234,10 +240,10 @@ def timeseries_query_per_sec(self,
             targets=targets,
             gridPos=gridPos,
             unit="Qps",
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_bytes_per_sec(self,
@@ -252,10 +258,10 @@ def timeseries_bytes_per_sec(self,
             targets=targets,
             gridPos=gridPos,
             unit="Bps",
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_bytes(self,
@@ -270,10 +276,10 @@ def timeseries_bytes(self,
             targets=targets,
             gridPos=gridPos,
             unit="bytes",
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_row(self, title, description, targets, legendCols=["mean"]):
@@ -284,10 +290,10 @@ def timeseries_row(self, title, description, targets, legendCols=["mean"]):
             targets=targets,
             gridPos=gridPos,
             unit="row",
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_ms(self, title, description, targets, legendCols=["mean"]):
@@ -297,10 +303,10 @@ def timeseries_ms(self, title, description, targets, legendCols=["mean"]):
             description=description,
             targets=targets,
             gridPos=gridPos,
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_kilobytes(self,
@@ -315,10 +321,10 @@ def timeseries_kilobytes(self,
             targets=targets,
             gridPos=gridPos,
             unit="kbytes",
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_dollar(self,
@@ -333,10 +339,10 @@ def timeseries_dollar(self,
             targets=targets,
             gridPos=gridPos,
             unit="$",
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_ops(self, title, description, targets, legendCols=["mean"]):
@@ -347,10 +353,10 @@ def timeseries_ops(self, title, description, targets, legendCols=["mean"]):
             targets=targets,
             gridPos=gridPos,
             unit="ops",
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_actor_ops(self,
@@ -365,10 +371,10 @@ def timeseries_actor_ops(self,
             targets=targets,
             gridPos=gridPos,
             unit="ops",
-            fillOpacity=0,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_actor_ops_small(self,
@@ -383,10 +389,10 @@ def timeseries_actor_ops_small(self,
             targets=targets,
             gridPos=gridPos,
             unit="ops",
-            fillOpacity=0,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_rowsps(self,
@@ -401,10 +407,10 @@ def timeseries_rowsps(self,
             targets=targets,
             gridPos=gridPos,
             unit="rows/s",
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_bytesps(self,
@@ -419,10 +425,10 @@ def timeseries_bytesps(self,
             targets=targets,
             gridPos=gridPos,
             unit="MB/s",
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
             legendCalcs=legendCols,
+            **self.common_options,
         )
 
     def timeseries_actor_rowsps(self, title, description, targets):
@@ -433,9 +439,9 @@ def timeseries_actor_rowsps(self, title, description, targets):
             targets=targets,
             gridPos=gridPos,
             unit="rows/s",
-            fillOpacity=0,
             legendDisplayMode="table",
             legendPlacement="right",
+            **self.common_options,
         )
 
     def timeseries_memory(self, title, description, targets):
@@ -446,7 +452,7 @@ def timeseries_memory(self, title, description, targets):
             targets=targets,
             gridPos=gridPos,
             unit="bytes",
-            fillOpacity=10,
+            **self.common_options,
         )
 
     def timeseries_cpu(self, title, description, targets):
@@ -457,7 +463,7 @@ def timeseries_cpu(self, title, description, targets):
             targets=targets,
             gridPos=gridPos,
             unit="percentunit",
-            fillOpacity=10,
+            **self.common_options,
         )
 
     def timeseries_latency_small(self, title, description, targets):
@@ -468,7 +474,7 @@ def timeseries_latency_small(self, title, description, targets):
             targets=targets,
             gridPos=gridPos,
             unit="s",
-            fillOpacity=10,
+            **self.common_options,
         )
 
     def timeseries_id(self, title, description, targets):
@@ -478,9 +484,9 @@ def timeseries_id(self, title, description, targets):
             description=description,
             targets=targets,
             gridPos=gridPos,
-            fillOpacity=10,
             legendDisplayMode="table",
             legendPlacement="right",
+            **self.common_options,
         )
 
     def table_info(self, title, description, targets, excluded_columns):
diff --git a/grafana/risingwave-dev-dashboard.dashboard.py b/grafana/risingwave-dev-dashboard.dashboard.py
index 497d74f04fbb2..14f7be4c8c2cb 100644
--- a/grafana/risingwave-dev-dashboard.dashboard.py
+++ b/grafana/risingwave-dev-dashboard.dashboard.py
@@ -633,6 +633,16 @@ def section_streaming(panels):
                 )
             ]
         ),
+        panels.timeseries_rowsps(
+            "Sink Throughput(rows/s)",
+            "The figure shows the number of rows output by each sink per second.",
+            [
+                panels.target(
+                    f"rate({metric('stream_sink_output_rows_counts')}[$__rate_interval])",
+                    "source={{source_name}} {{source_id}} @ {{instance}}",
+                ),
+            ],
+        ),
         panels.timeseries_rowsps(
             "Backfill Snapshot Read Throughput(rows)",
             "Total number of rows that have been read from the backfill snapshot",
@@ -848,156 +858,6 @@ def section_streaming_actors(outer_panels):
                         ),
                     ],
                 ),
-                panels.timeseries_actor_latency_small(
-                    "Tokio: Actor Fast Poll Time",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_fast_poll_duration')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_ops_small(
-                    "Tokio: Actor Fast Poll Count",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_fast_poll_cnt')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_latency_small(
-                    "Tokio: Actor Fast Poll Avg Time",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_fast_poll_duration')}[$__rate_interval]) / rate({metric('stream_actor_fast_poll_cnt')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_latency_small(
-                    "Tokio: Actor Slow Poll Total Time",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_slow_poll_duration')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_ops_small(
-                    "Tokio: Actor Slow Poll Count",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_slow_poll_cnt')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_latency_small(
-                    "Tokio: Actor Slow Poll Avg Time",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_slow_poll_duration')}[$__rate_interval]) / rate({metric('stream_actor_slow_poll_cnt')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_latency_small(
-                    "Tokio: Actor Poll Total Time",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_poll_duration')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_ops_small(
-                    "Tokio: Actor Poll Count",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_poll_cnt')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_latency_small(
-                    "Tokio: Actor Poll Avg Time",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_poll_duration')}[$__rate_interval]) / rate({metric('stream_actor_poll_cnt')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_latency_small(
-                    "Tokio: Actor Idle Total Time",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_idle_duration')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_ops_small(
-                    "Tokio: Actor Idle Count",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_idle_cnt')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_latency_small(
-                    "Tokio: Actor Idle Avg Time",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_idle_duration')}[$__rate_interval]) / rate({metric('stream_actor_idle_cnt')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_latency_small(
-                    "Tokio: Actor Scheduled Total Time",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_scheduled_duration')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_ops_small(
-                    "Tokio: Actor Scheduled Count",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_scheduled_cnt')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
-                panels.timeseries_actor_latency_small(
-                    "Tokio: Actor Scheduled Avg Time",
-                    "",
-                    [
-                        panels.target(
-                            f"rate({metric('stream_actor_scheduled_duration')}[$__rate_interval]) / rate({metric('stream_actor_scheduled_cnt')}[$__rate_interval]) > 0",
-                            "{{actor_id}}",
-                        ),
-                    ],
-                ),
                 panels.timeseries_actor_ops(
                     "Join Executor Cache",
                     "",
@@ -1157,6 +1017,165 @@ def section_streaming_actors(outer_panels):
         )
     ]
 
+def section_streaming_actors_tokio(outer_panels):
+    panels = outer_panels.sub_panel()
+    return [
+        outer_panels.row_collapsed(
+            "Streaming Actors (Tokio)",
+            [
+                panels.timeseries_actor_latency_small(
+                    "Tokio: Actor Fast Poll Time",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_fast_poll_duration')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_ops_small(
+                    "Tokio: Actor Fast Poll Count",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_fast_poll_cnt')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_latency_small(
+                    "Tokio: Actor Fast Poll Avg Time",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_fast_poll_duration')}[$__rate_interval]) / rate({metric('stream_actor_fast_poll_cnt')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_latency_small(
+                    "Tokio: Actor Slow Poll Total Time",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_slow_poll_duration')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_ops_small(
+                    "Tokio: Actor Slow Poll Count",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_slow_poll_cnt')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_latency_small(
+                    "Tokio: Actor Slow Poll Avg Time",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_slow_poll_duration')}[$__rate_interval]) / rate({metric('stream_actor_slow_poll_cnt')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_latency_small(
+                    "Tokio: Actor Poll Total Time",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_poll_duration')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_ops_small(
+                    "Tokio: Actor Poll Count",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_poll_cnt')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_latency_small(
+                    "Tokio: Actor Poll Avg Time",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_poll_duration')}[$__rate_interval]) / rate({metric('stream_actor_poll_cnt')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_latency_small(
+                    "Tokio: Actor Idle Total Time",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_idle_duration')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_ops_small(
+                    "Tokio: Actor Idle Count",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_idle_cnt')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_latency_small(
+                    "Tokio: Actor Idle Avg Time",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_idle_duration')}[$__rate_interval]) / rate({metric('stream_actor_idle_cnt')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_latency_small(
+                    "Tokio: Actor Scheduled Total Time",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_scheduled_duration')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_ops_small(
+                    "Tokio: Actor Scheduled Count",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_scheduled_cnt')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+                panels.timeseries_actor_latency_small(
+                    "Tokio: Actor Scheduled Avg Time",
+                    "",
+                    [
+                        panels.target(
+                            f"rate({metric('stream_actor_scheduled_duration')}[$__rate_interval]) / rate({metric('stream_actor_scheduled_cnt')}[$__rate_interval]) > 0",
+                            "{{actor_id}}",
+                        ),
+                    ],
+                ),
+            ]
+        )
+    ]
 
 def section_streaming_exchange(outer_panels):
     panels = outer_panels.sub_panel()
@@ -2449,6 +2468,7 @@ def section_connector_node(outer_panels):
         *section_recovery_node(panels),
         *section_streaming(panels),
         *section_streaming_actors(panels),
+        *section_streaming_actors_tokio(panels),
         *section_streaming_exchange(panels),
         *section_streaming_errors(panels),
         *section_batch(panels),
diff --git a/grafana/risingwave-dev-dashboard.json b/grafana/risingwave-dev-dashboard.json
index e015e4d632f7d..54ce16303ed18 100644
--- a/grafana/risingwave-dev-dashboard.json
+++ b/grafana/risingwave-dev-dashboard.json
@@ -1 +1 @@
-{"__inputs":[],"annotations":{"list":[]},"description":"RisingWave Dev Dashboard","editable":true,"gnetId":null,"hideControls":false,"id":null,"links":[],"panels":[{"cacheTimeout":null,"collapsed":false,"datasource":null,"description":null,"editable":true,"error":false,"fieldConfig":{"defaults":{"thresholds":{"mode":"absolute","steps":[]}}},"gridPos":{"h":1,"w":24,"x":0,"y":0},"height":null,"hideTimeOverride":false,"id":1,"interval":null,"links":[],"maxDataPoints":100,"maxPerRow":null,"minSpan":null,"panels":[],"repeat":null,"repeatDirection":null,"span":null,"targets":[],"timeFrom":null,"timeShift":null,"title":"Actor/Table Id Info","transformations":[],"transparent":false,"type":"row"},{"cacheTimeout":null,"color":{"mode":"thresholds"},"columns":[],"datasource":null,"description":"Mapping from actor id to fragment 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diff --git a/grafana/risingwave-user-dashboard.dashboard.py b/grafana/risingwave-user-dashboard.dashboard.py
index 00c23c5f89a50..7874fa8f7c70f 100644
--- a/grafana/risingwave-user-dashboard.dashboard.py
+++ b/grafana/risingwave-user-dashboard.dashboard.py
@@ -66,6 +66,16 @@ def section_overview(panels):
                 )
             ],
         ),
+        panels.timeseries_rowsps(
+            "Aggregated Sink Throughput(rows/s)",
+            "The figure shows the number of rows output by each sink per second.",
+            [
+                panels.target(
+                    f"sum(rate({metric('stream_sink_output_rows_counts')}[$__rate_interval])) by (source_name)",
+                    "{{source_name}}",
+                ),
+            ],
+        ),
         panels.timeseries_latency(
             "Barrier Latency",
             "The time that the data between two consecutive barriers gets fully processed, i.e. the computation "
diff --git a/grafana/risingwave-user-dashboard.json b/grafana/risingwave-user-dashboard.json
index 587ed5743e03d..69c9ef20fa657 100644
--- a/grafana/risingwave-user-dashboard.json
+++ b/grafana/risingwave-user-dashboard.json
@@ -1 +1 @@
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mode","transformations":[],"transparent":false,"type":"timeseries"},{"cacheTimeout":null,"datasource":null,"description":"","editable":true,"error":false,"fieldConfig":{"defaults":{"color":{"mode":"palette-classic"},"custom":{"axisLabel":"","axisPlacement":"auto","barAlignment":0,"drawStyle":"line","fillOpacity":10,"gradientMode":"none","hideFrom":{"legend":false,"tooltip":false,"viz":false},"lineInterpolation":"linear","lineWidth":1,"pointSize":5,"scaleDistribution":{"log":2,"type":"linear"},"showPoints":"auto","spanNulls":false,"stacking":{},"thresholdsStyle":{"mode":"off"}},"mappings":[],"thresholds":{"mode":"absolute","steps":[]},"unit":"s"},"overrides":[]},"gridPos":{"h":8,"w":12,"x":12,"y":8},"height":null,"hideTimeOverride":false,"id":44,"interval":"1s","links":[],"maxDataPoints":1000,"maxPerRow":null,"minSpan":null,"options":{"legend":{"calcs":["mean"],"displayMode":"table","placement":"right"},"tooltip":{"mode":"single"}},"repeat":null,"repeatDirection":null,"span":null,"targets":[{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"histogram_quantile(0.5, sum(rate(distributed_query_latency_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p50 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""},{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"histogram_quantile(0.9, sum(rate(distributed_query_latency_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p90 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""},{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"histogram_quantile(0.95, sum(rate(distributed_query_latency_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p99 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""}],"timeFrom":null,"timeShift":null,"title":"Query Latency in Distributed Execution Mode","transformations":[],"transparent":false,"type":"timeseries"},{"cacheTimeout":null,"datasource":null,"description":"","editable":true,"error":false,"fieldConfig":{"defaults":{"color":{"mode":"palette-classic"},"custom":{"axisLabel":"","axisPlacement":"auto","barAlignment":0,"drawStyle":"line","fillOpacity":10,"gradientMode":"none","hideFrom":{"legend":false,"tooltip":false,"viz":false},"lineInterpolation":"linear","lineWidth":1,"pointSize":5,"scaleDistribution":{"log":2,"type":"linear"},"showPoints":"auto","spanNulls":false,"stacking":{},"thresholdsStyle":{"mode":"off"}},"mappings":[],"thresholds":{"mode":"absolute","steps":[]},"unit":"s"},"overrides":[]},"gridPos":{"h":8,"w":12,"x":0,"y":16},"height":null,"hideTimeOverride":false,"id":45,"interval":"1s","links":[],"maxDataPoints":1000,"maxPerRow":null,"minSpan":null,"options":{"legend":{"calcs":["mean"],"displayMode":"table","placement":"right"},"tooltip":{"mode":"single"}},"repeat":null,"repeatDirection":null,"span":null,"targets":[{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"histogram_quantile(0.5, sum(rate(frontend_latency_local_execution_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p50 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""},{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"histogram_quantile(0.9, sum(rate(frontend_latency_local_execution_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p90 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""},{"datasource":{"type":"prometheus","uid":"risedev-prometheus"},"expr":"histogram_quantile(0.95, sum(rate(frontend_latency_local_execution_bucket[$__rate_interval])) by (le, job, instance))","format":"time_series","hide":false,"instant":false,"interval":"","intervalFactor":2,"legendFormat":"p99 - {{job}} @ {{instance}}","metric":"","refId":"","step":10,"target":""}],"timeFrom":null,"timeShift":null,"title":"Query Latency in Local Execution Mode","transformations":[],"transparent":false,"type":"timeseries"}],"repeat":null,"repeatDirection":null,"span":null,"targets":[],"timeFrom":null,"timeShift":null,"title":"Batch","transformations":[],"transparent":false,"type":"row"}],"refresh":"10s","rows":[],"schemaVersion":12,"sharedCrosshair":true,"style":"dark","tags":["risingwave"],"templating":{"list":[]},"time":{"from":"now-30m","to":"now"},"timepicker":{"hidden":false,"refresh_intervals":["5s","10s","30s","1m","5m","15m","30m","1h","2h","1d"],"time_options":["5m","15m","1h","6h","12h","24h","2d","7d","30d"]},"timezone":"browser","title":"risingwave_dashboard","uid":"Fcy3uV1nz","version":0}
diff --git a/java/connector-node/risingwave-connector-service/src/main/java/com/risingwave/connector/source/common/MySqlValidator.java b/java/connector-node/risingwave-connector-service/src/main/java/com/risingwave/connector/source/common/MySqlValidator.java
index efaaa33fe4952..9cfafa91e25b2 100644
--- a/java/connector-node/risingwave-connector-service/src/main/java/com/risingwave/connector/source/common/MySqlValidator.java
+++ b/java/connector-node/risingwave-connector-service/src/main/java/com/risingwave/connector/source/common/MySqlValidator.java
@@ -161,7 +161,33 @@ private void validateTableSchema() throws SQLException {
     }
 
     private void validatePrivileges() throws SQLException {
-        // TODO: validate MySQL user privileges
+        String[] privilegesRequired = {
+            "SELECT",
+            "RELOAD",
+            "SHOW DATABASES",
+            "REPLICATION SLAVE",
+            "REPLICATION CLIENT",
+            "LOCK TABLES"
+        };
+        try (var stmt = jdbcConnection.createStatement()) {
+            var res = stmt.executeQuery(ValidatorUtils.getSql("mysql.grants"));
+            while (res.next()) {
+                String grants = res.getString(1).toUpperCase();
+                // all privileges granted, check passed
+                if (grants.contains("ALL")) {
+                    break;
+                }
+                // check whether each privilege is granted
+                for (String privilege : privilegesRequired) {
+                    if (!grants.contains(privilege)) {
+                        throw ValidatorUtils.invalidArgument(
+                                String.format(
+                                        "MySQL user does not have privilege %s, which is needed for debezium connector",
+                                        privilege));
+                    }
+                }
+            }
+        }
     }
 
     @Override
diff --git a/java/connector-node/risingwave-connector-service/src/main/resources/validate_sql.properties b/java/connector-node/risingwave-connector-service/src/main/resources/validate_sql.properties
index aec6606cc01f0..53d300a8e6aeb 100644
--- a/java/connector-node/risingwave-connector-service/src/main/resources/validate_sql.properties
+++ b/java/connector-node/risingwave-connector-service/src/main/resources/validate_sql.properties
@@ -3,6 +3,7 @@ mysql.bin_format=show variables like 'binlog_format'
 mysql.bin_row_image=show variables like 'binlog_row_image'
 mysql.table=SELECT count(*) FROM information_schema.TABLES WHERE TABLE_SCHEMA = ? AND TABLE_NAME = ?
 mysql.table_schema=SELECT COLUMN_NAME, DATA_TYPE, COLUMN_KEY FROM information_schema.COLUMNS WHERE TABLE_SCHEMA = ? AND TABLE_NAME = ? ORDER BY ORDINAL_POSITION
+mysql.grants=SHOW GRANTS FOR CURRENT_USER()
 postgres.wal=show wal_level
 postgres.table=SELECT EXISTS ( SELECT FROM pg_tables WHERE schemaname = ? AND tablename = ?)
 postgres.pk=SELECT a.attname, format_type(a.atttypid, a.atttypmod) AS data_type FROM pg_index i JOIN pg_attribute a ON a.attrelid = i.indrelid AND a.attnum = ANY(i.indkey) WHERE i.indrelid = ?::regclass AND i.indisprimary
diff --git a/java/connector-node/risingwave-source-test/src/test/java/com/risingwave/connector/MySQLSourceTest.java b/java/connector-node/risingwave-source-test/src/test/java/com/risingwave/connector/MySQLSourceTest.java
index 3b56dcb6f056f..dbf2a2ab152b0 100644
--- a/java/connector-node/risingwave-source-test/src/test/java/com/risingwave/connector/MySQLSourceTest.java
+++ b/java/connector-node/risingwave-source-test/src/test/java/com/risingwave/connector/MySQLSourceTest.java
@@ -17,7 +17,9 @@
 import static org.assertj.core.api.Assertions.*;
 import static org.junit.Assert.assertEquals;
 
+import com.risingwave.proto.ConnectorServiceProto;
 import com.risingwave.proto.ConnectorServiceProto.*;
+import com.risingwave.proto.Data;
 import io.grpc.*;
 import java.io.IOException;
 import java.sql.Connection;
@@ -27,10 +29,7 @@
 import java.util.List;
 import java.util.concurrent.*;
 import javax.sql.DataSource;
-import org.junit.AfterClass;
-import org.junit.BeforeClass;
-import org.junit.Ignore;
-import org.junit.Test;
+import org.junit.*;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.testcontainers.containers.MySQLContainer;
@@ -139,8 +138,75 @@ public void testLines() throws InterruptedException, SQLException {
             assertEquals(10000, count);
         } catch (ExecutionException e) {
             fail("Execution exception: ", e);
+        } finally {
+            // cleanup
+            query = testClient.sqlStmts.getProperty("tpch.drop.orders");
+            SourceTestClient.performQuery(connection, query);
+            connection.close();
+        }
+    }
+
+    // test whether validation catches permission errors
+    @Test
+    public void testPermissionCheck() throws SQLException {
+        // user Root creates a superuser debezium
+        Connection connRoot = SourceTestClient.connect(mysqlDataSource);
+        String query = "CREATE USER debezium IDENTIFIED BY '" + mysql.getPassword() + "'";
+        SourceTestClient.performQuery(connRoot, query);
+        query =
+                "GRANT SELECT, RELOAD, SHOW DATABASES, REPLICATION SLAVE, REPLICATION CLIENT ON *.* TO 'debezium'";
+        SourceTestClient.performQuery(connRoot, query);
+        // user debezium connects to Mysql
+        DataSource dbzDataSource =
+                SourceTestClient.getDataSource(
+                        mysql.getJdbcUrl(),
+                        "debezium",
+                        mysql.getPassword(),
+                        mysql.getDriverClassName());
+        Connection connDbz = SourceTestClient.connect(dbzDataSource);
+        query =
+                "CREATE TABLE IF NOT EXISTS orders (o_key BIGINT NOT NULL, o_val INT, PRIMARY KEY (o_key))";
+        SourceTestClient.performQuery(connDbz, query);
+        ConnectorServiceProto.TableSchema tableSchema =
+                ConnectorServiceProto.TableSchema.newBuilder()
+                        .addColumns(
+                                ConnectorServiceProto.TableSchema.Column.newBuilder()
+                                        .setName("o_key")
+                                        .setDataType(Data.DataType.TypeName.INT64)
+                                        .build())
+                        .addColumns(
+                                ConnectorServiceProto.TableSchema.Column.newBuilder()
+                                        .setName("o_val")
+                                        .setDataType(Data.DataType.TypeName.INT32)
+                                        .build())
+                        .addPkIndices(0)
+                        .build();
+
+        try {
+            var resp =
+                    testClient.validateSource(
+                            mysql.getJdbcUrl(),
+                            mysql.getHost(),
+                            "debezium",
+                            mysql.getPassword(),
+                            SourceType.MYSQL,
+                            tableSchema,
+                            "test",
+                            "orders");
+            assertEquals(
+                    "INTERNAL: MySQL user does not have privilege LOCK TABLES, which is needed for debezium connector",
+                    resp.getError().getErrorMessage());
+        } catch (Exception e) {
+            Assert.fail("validate rpc fail: " + e.getMessage());
+        } finally {
+            // cleanup
+            query = testClient.sqlStmts.getProperty("tpch.drop.orders");
+            SourceTestClient.performQuery(connDbz, query);
+            query = "DROP USER IF EXISTS debezium";
+            SourceTestClient.performQuery(connRoot, query);
+            connDbz.close();
+            connRoot.close();
         }
-        connection.close();
     }
 
     // generates test cases for the risingwave debezium parser
diff --git a/java/connector-node/risingwave-source-test/src/test/java/com/risingwave/connector/PostgresSourceTest.java b/java/connector-node/risingwave-source-test/src/test/java/com/risingwave/connector/PostgresSourceTest.java
index ffb5dab5b626a..57349479ba7f0 100644
--- a/java/connector-node/risingwave-source-test/src/test/java/com/risingwave/connector/PostgresSourceTest.java
+++ b/java/connector-node/risingwave-source-test/src/test/java/com/risingwave/connector/PostgresSourceTest.java
@@ -146,7 +146,7 @@ public void testLines() throws Exception {
             Assert.fail("validate rpc fail: " + e.getMessage());
         } finally {
             // cleanup
-            query = "DROP TABLE orders";
+            query = testClient.sqlStmts.getProperty("tpch.drop.orders");
             SourceTestClient.performQuery(connection, query);
             connection.close();
         }
@@ -227,7 +227,7 @@ public void testPermissionCheck() throws SQLException {
             Assert.fail("validate rpc fail: " + e.getMessage());
         } finally {
             // cleanup
-            query = "DROP TABLE orders";
+            query = testClient.sqlStmts.getProperty("tpch.drop.orders");
             SourceTestClient.performQuery(connDbz, query);
             query = "DROP USER debezium";
             SourceTestClient.performQuery(connPg, query);
diff --git a/java/connector-node/risingwave-source-test/src/test/resources/stored_queries.properties b/java/connector-node/risingwave-source-test/src/test/resources/stored_queries.properties
index 20acafedebae5..94811a495062b 100644
--- a/java/connector-node/risingwave-source-test/src/test/resources/stored_queries.properties
+++ b/java/connector-node/risingwave-source-test/src/test/resources/stored_queries.properties
@@ -1,3 +1,4 @@
 mysql.bin_log=show variables like 'log_bin'
 postgres.wal=show wal_level
-tpch.create.orders=CREATE TABLE IF NOT EXISTS orders (O_ORDERKEY BIGINT NOT NULL, O_CUSTKEY BIGINT NOT NULL, O_ORDERSTATUS CHAR(1) NOT NULL, O_TOTALPRICE DECIMAL(15, 2) NOT NULL, O_ORDERDATE DATE NOT NULL, O_ORDERPRIORITY CHAR(15) NOT NULL, O_CLERK CHAR(15) NOT NULL, O_SHIPPRIORITY BIGINT NOT NULL, O_COMMENT VARCHAR(79) NOT NULL, PRIMARY KEY (O_ORDERKEY))
\ No newline at end of file
+tpch.create.orders=CREATE TABLE IF NOT EXISTS orders (O_ORDERKEY BIGINT NOT NULL, O_CUSTKEY BIGINT NOT NULL, O_ORDERSTATUS CHAR(1) NOT NULL, O_TOTALPRICE DECIMAL(15, 2) NOT NULL, O_ORDERDATE DATE NOT NULL, O_ORDERPRIORITY CHAR(15) NOT NULL, O_CLERK CHAR(15) NOT NULL, O_SHIPPRIORITY BIGINT NOT NULL, O_COMMENT VARCHAR(79) NOT NULL, PRIMARY KEY (O_ORDERKEY))
+tpch.drop.orders=DROP TABLE IF EXISTS orders
\ No newline at end of file
diff --git a/src/connector/src/source/kafka/enumerator/client.rs b/src/connector/src/source/kafka/enumerator/client.rs
index cb2d8fa705b53..b313be7acc203 100644
--- a/src/connector/src/source/kafka/enumerator/client.rs
+++ b/src/connector/src/source/kafka/enumerator/client.rs
@@ -13,6 +13,7 @@
 // limitations under the License.
 
 use std::collections::HashMap;
+use std::time::Duration;
 
 use anyhow::anyhow;
 use async_trait::async_trait;
@@ -22,9 +23,7 @@ use rdkafka::{Offset, TopicPartitionList};
 
 use crate::source::base::SplitEnumerator;
 use crate::source::kafka::split::KafkaSplit;
-use crate::source::kafka::{
-    KafkaProperties, PrivateLinkConsumerContext, KAFKA_ISOLATION_LEVEL, KAFKA_SYNC_CALL_TIMEOUT,
-};
+use crate::source::kafka::{KafkaProperties, PrivateLinkConsumerContext, KAFKA_ISOLATION_LEVEL};
 
 #[derive(Debug, Copy, Clone, Eq, PartialEq)]
 pub enum KafkaEnumeratorOffset {
@@ -42,6 +41,8 @@ pub struct KafkaSplitEnumerator {
 
     // maybe used in the future for batch processing
     stop_offset: KafkaEnumeratorOffset,
+
+    sync_call_timeout: Duration,
 }
 
 impl KafkaSplitEnumerator {}
@@ -92,6 +93,7 @@ impl SplitEnumerator for KafkaSplitEnumerator {
             client,
             start_offset: scan_start_offset,
             stop_offset: KafkaEnumeratorOffset::None,
+            sync_call_timeout: properties.sync_call_timeout,
         })
     }
 
@@ -165,13 +167,12 @@ impl KafkaSplitEnumerator {
             for partition in &topic_partitions {
                 let (low, high) = self
                     .client
-                    .fetch_watermarks(self.topic.as_str(), *partition, KAFKA_SYNC_CALL_TIMEOUT)
+                    .fetch_watermarks(self.topic.as_str(), *partition, self.sync_call_timeout)
                     .await?;
                 ret.insert(partition, (low - 1, high));
             }
             ret
         };
-        // println!("Watermark: {:?}", watermarks);
 
         Ok(topic_partitions
             .iter()
@@ -223,7 +224,7 @@ impl KafkaSplitEnumerator {
                 for partition in partitions {
                     let (_, high_watermark) = self
                         .client
-                        .fetch_watermarks(self.topic.as_str(), *partition, KAFKA_SYNC_CALL_TIMEOUT)
+                        .fetch_watermarks(self.topic.as_str(), *partition, self.sync_call_timeout)
                         .await?;
                     map.insert(*partition, Some(high_watermark));
                 }
@@ -249,7 +250,7 @@ impl KafkaSplitEnumerator {
                 for partition in partitions {
                     let (low_watermark, high_watermark) = self
                         .client
-                        .fetch_watermarks(self.topic.as_str(), *partition, KAFKA_SYNC_CALL_TIMEOUT)
+                        .fetch_watermarks(self.topic.as_str(), *partition, self.sync_call_timeout)
                         .await?;
                     let offset = match self.start_offset {
                         KafkaEnumeratorOffset::Earliest => low_watermark - 1,
@@ -283,7 +284,7 @@ impl KafkaSplitEnumerator {
 
         let offsets = self
             .client
-            .offsets_for_times(tpl, KAFKA_SYNC_CALL_TIMEOUT)
+            .offsets_for_times(tpl, self.sync_call_timeout)
             .await?;
 
         let mut result = HashMap::with_capacity(partitions.len());
@@ -299,7 +300,7 @@ impl KafkaSplitEnumerator {
                         .fetch_watermarks(
                             self.topic.as_str(),
                             elem.partition(),
-                            KAFKA_SYNC_CALL_TIMEOUT,
+                            self.sync_call_timeout,
                         )
                         .await?;
                     result.insert(elem.partition(), Some(high_watermark));
@@ -314,7 +315,7 @@ impl KafkaSplitEnumerator {
         // for now, we only support one topic
         let metadata = self
             .client
-            .fetch_metadata(Some(self.topic.as_str()), KAFKA_SYNC_CALL_TIMEOUT)
+            .fetch_metadata(Some(self.topic.as_str()), self.sync_call_timeout)
             .await?;
 
         let topic_meta = match metadata.topics() {
diff --git a/src/connector/src/source/kafka/mod.rs b/src/connector/src/source/kafka/mod.rs
index ad6fccb49481b..878f4ff8e78a3 100644
--- a/src/connector/src/source/kafka/mod.rs
+++ b/src/connector/src/source/kafka/mod.rs
@@ -27,6 +27,7 @@ pub use source::*;
 pub use split::*;
 
 use crate::common::KafkaCommon;
+use crate::deserialize_duration_from_string;
 pub const KAFKA_CONNECTOR: &str = "kafka";
 pub const KAFKA_PROPS_BROKER_KEY: &str = "properties.bootstrap.server";
 pub const KAFKA_PROPS_BROKER_KEY_ALIAS: &str = "kafka.brokers";
@@ -57,9 +58,24 @@ pub struct KafkaProperties {
     #[serde(rename = "properties.group.id", alias = "kafka.consumer.group")]
     pub consumer_group: Option<String>,
 
+    /// This parameter is used to tell KafkaSplitReader to produce `UpsertMessage`s, which
+    /// combine both key and value fields of the Kafka message.
+    /// TODO: Currently, `Option<bool>` can not be parsed here.
+    #[serde(rename = "upsert")]
+    pub upsert: Option<String>,
+
+    #[serde(
+        rename = "properties.sync.call.timeout",
+        deserialize_with = "deserialize_duration_from_string",
+        default = "default_kafka_sync_call_timeout"
+    )]
+    pub sync_call_timeout: Duration,
+
     #[serde(flatten)]
     pub common: KafkaCommon,
 }
 
-const KAFKA_SYNC_CALL_TIMEOUT: Duration = Duration::from_secs(1);
+const fn default_kafka_sync_call_timeout() -> Duration {
+    Duration::from_secs(5)
+}
 const KAFKA_ISOLATION_LEVEL: &str = "read_committed";
diff --git a/src/expr/Cargo.toml b/src/expr/Cargo.toml
index 1b87ffd9b53f9..bc79ecdd5de83 100644
--- a/src/expr/Cargo.toml
+++ b/src/expr/Cargo.toml
@@ -20,6 +20,7 @@ anyhow = "1"
 arrow-array = "36"
 arrow-schema = "36"
 async-trait = "0.1"
+auto_enums = "0.8"
 chrono = { version = "0.4", default-features = false, features = ["clock", "std"] }
 chrono-tz = { version = "0.7", features = ["case-insensitive"] }
 ctor = "0.1"
diff --git a/src/expr/src/vector_op/string_to_array.rs b/src/expr/src/vector_op/string_to_array.rs
index 442ac7988f72d..7e2d36aed5142 100644
--- a/src/expr/src/vector_op/string_to_array.rs
+++ b/src/expr/src/vector_op/string_to_array.rs
@@ -12,27 +12,25 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
+use auto_enums::auto_enum;
 use itertools::Itertools;
 use risingwave_common::array::ListValue;
 use risingwave_common::types::ScalarImpl;
 use risingwave_expr_macro::function;
 
-fn string_to_array_inner(s: &str, sep: Option<&str>) -> Vec<String> {
-    if s.is_empty() {
-        vec![]
-    } else {
-        sep.map_or(
-            s.chars().map(|x| x.to_string()).collect_vec(),
-            |sep| match sep.is_empty() {
-                true => vec![s.to_string()],
-                false => s
-                    .split(sep)
-                    .collect_vec()
-                    .into_iter()
-                    .map(|x| x.to_string())
-                    .collect_vec(),
-            },
-        )
+#[auto_enum(Iterator)]
+fn string_to_array_inner<'a>(
+    s: &'a str,
+    sep: Option<&'a str>,
+) -> impl Iterator<Item = String> + 'a {
+    match s.is_empty() {
+        true => std::iter::empty(),
+        #[nested]
+        _ => match sep {
+            Some(sep) if sep.is_empty() => std::iter::once(s.to_string()),
+            Some(sep) => s.split(sep).map(|x| x.to_string()),
+            None => s.chars().map(|x| x.to_string()),
+        },
     }
 }
 
@@ -42,7 +40,6 @@ pub fn string_to_array2(s: Option<&str>, sep: Option<&str>) -> Option<ListValue>
     s.map(|s| {
         ListValue::new(
             string_to_array_inner(s, sep)
-                .into_iter()
                 .map(|x| Some(ScalarImpl::Utf8(x.into())))
                 .collect_vec(),
         )
@@ -56,16 +53,21 @@ pub fn string_to_array3(
     null: Option<&str>,
 ) -> Option<ListValue> {
     s.map(|s| {
-        null.map_or(string_to_array2(Some(s), sep).unwrap(), |null| {
-            ListValue::new(
-                string_to_array_inner(s, sep)
-                    .into_iter()
-                    .map(|x| match x == null {
-                        true => None,
-                        _ => Some(ScalarImpl::Utf8(x.into())),
-                    })
-                    .collect_vec(),
-            )
-        })
+        null.map_or_else(
+            || string_to_array2(Some(s), sep).unwrap(),
+            |null| {
+                ListValue::new(
+                    string_to_array_inner(s, sep)
+                        .map(|x| {
+                            if x == null {
+                                None
+                            } else {
+                                Some(ScalarImpl::Utf8(x.into()))
+                            }
+                        })
+                        .collect_vec(),
+                )
+            },
+        )
     })
 }
diff --git a/src/stream/src/executor/monitor/streaming_stats.rs b/src/stream/src/executor/monitor/streaming_stats.rs
index 4598ef480a9f7..5f915299058c3 100644
--- a/src/stream/src/executor/monitor/streaming_stats.rs
+++ b/src/stream/src/executor/monitor/streaming_stats.rs
@@ -78,6 +78,8 @@ pub struct StreamingMetrics {
 
     pub sink_commit_duration: HistogramVec,
 
+    pub sink_output_row_count: GenericCounterVec<AtomicU64>,
+
     // Memory management
     // FIXME(yuhao): use u64 here
     pub lru_current_watermark_time_ms: IntGauge,
@@ -415,6 +417,14 @@ impl StreamingMetrics {
         )
         .unwrap();
 
+        let sink_output_row_count = register_int_counter_vec_with_registry!(
+            "stream_sink_output_rows_counts",
+            "Total number of rows that have been output to sink",
+            &["sink_id", "sink_name"],
+            registry
+        )
+        .unwrap();
+
         let lru_current_watermark_time_ms = register_int_gauge_with_registry!(
             "lru_current_watermark_time_ms",
             "Current LRU manager watermark time(ms)",
@@ -522,6 +532,7 @@ impl StreamingMetrics {
             barrier_inflight_latency,
             barrier_sync_latency,
             sink_commit_duration,
+            sink_output_row_count,
             lru_current_watermark_time_ms,
             lru_physical_now_ms,
             lru_runtime_loop_count,
diff --git a/src/stream/src/executor/sink.rs b/src/stream/src/executor/sink.rs
index aba6a01fcf039..24db219a0abb8 100644
--- a/src/stream/src/executor/sink.rs
+++ b/src/stream/src/executor/sink.rs
@@ -18,6 +18,7 @@ use std::time::Instant;
 use futures::stream::select;
 use futures::{FutureExt, StreamExt};
 use futures_async_stream::try_stream;
+use prometheus::core::{AtomicU64, GenericCounter};
 use prometheus::Histogram;
 use risingwave_common::array::{Op, StreamChunk};
 use risingwave_common::catalog::Schema;
@@ -123,10 +124,14 @@ impl<F: LogStoreFactory> SinkExecutor<F> {
     }
 
     fn execute_inner(self) -> BoxedMessageStream {
-        let metrics = self
+        let sink_commit_duration_metrics = self
             .metrics
             .sink_commit_duration
             .with_label_values(&[self.identity.as_str(), self.config.get_connector()]);
+        let sink_throughput_metrics = self
+            .metrics
+            .sink_output_row_count
+            .with_label_values(&[self.identity.as_str(), self.config.get_connector()]);
 
         let write_log_stream = Self::execute_write_log(
             self.input,
@@ -137,7 +142,12 @@ impl<F: LogStoreFactory> SinkExecutor<F> {
         );
 
         dispatch_sink!(self.sink, sink, {
-            let consume_log_stream = Self::execute_consume_log(sink, self.log_reader, metrics);
+            let consume_log_stream = Self::execute_consume_log(
+                sink,
+                self.log_reader,
+                sink_commit_duration_metrics,
+                sink_throughput_metrics,
+            );
             select(consume_log_stream.into_stream(), write_log_stream).boxed()
         })
     }
@@ -204,6 +214,7 @@ impl<F: LogStoreFactory> SinkExecutor<F> {
         mut sink: S,
         mut log_reader: R,
         sink_commit_duration_metrics: Histogram,
+        sink_throughput_metrics: GenericCounter<AtomicU64>,
     ) -> StreamExecutorResult<Message> {
         log_reader.init().await?;
 
@@ -255,6 +266,7 @@ impl<F: LogStoreFactory> SinkExecutor<F> {
                         sink.abort().await?;
                         return Err(e.into());
                     }
+                    sink_throughput_metrics.inc_by(chunk.cardinality() as u64);
                 }
                 LogStoreReadItem::Barrier { is_checkpoint } => {
                     state = match state {