Add vfsreadlat.py BCC example

BCC-Examples/hello_perf_output.py

@@ -1,14 +1,14 @@
 from pythonbpf import bpf, map, struct, section, bpfglobal, BPF
 from pythonbpf.helper import ktime, pid, comm
 from pythonbpf.maps import PerfEventArray
-from ctypes import c_void_p, c_int64, c_uint64
+from ctypes import c_void_p, c_int64
 
 
 @bpf
 @struct
 class data_t:
-    pid: c_uint64
-    ts: c_uint64
+    pid: c_int64
+    ts: c_int64
     comm: str(16)  # type: ignore [valid-type]
 
 

BCC-Examples/vfsreadlat.py

@@ -0,0 +1,127 @@
+from pythonbpf import bpf, map, struct, section, bpfglobal, BPF
+from pythonbpf.helper import ktime, pid
+from pythonbpf.maps import HashMap, PerfEventArray
+from ctypes import c_void_p, c_uint64
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+@bpf
+@struct
+class latency_event:
+    pid: c_uint64
+    delta_us: c_uint64  # Latency in microseconds
+
+
+@bpf
+@map
+def start() -> HashMap:
+    return HashMap(key=c_uint64, value=c_uint64, max_entries=10240)
+
+
+@bpf
+@map
+def events() -> PerfEventArray:
+    return PerfEventArray(key_size=c_uint64, value_size=c_uint64)
+
+
+@bpf
+@section("kprobe/vfs_read")
+def do_entry(ctx: c_void_p) -> c_uint64:
+    p, ts = pid(), ktime()
+    start.update(p, ts)
+    return 0  # type: ignore [return-value]
+
+
+@bpf
+@section("kretprobe/vfs_read")
+def do_return(ctx: c_void_p) -> c_uint64:
+    p = pid()
+    tsp = start.lookup(p)
+
+    if tsp:
+        delta_ns = ktime() - tsp
+
+        # Only track if latency > 1 microsecond
+        if delta_ns > 1000:
+            evt = latency_event()
+            evt.pid, evt.delta_us = p, delta_ns // 1000
+            events.output(evt)
+
+        start.delete(p)
+
+    return 0  # type: ignore [return-value]
+
+
+@bpf
+@bpfglobal
+def LICENSE() -> str:
+    return "GPL"
+
+
+# Load BPF
+print("Loading BPF program...")
+b = BPF()
+b.load()
+b.attach_all()
+
+# Collect latencies
+latencies = []
+
+
+def callback(cpu, event):
+    latencies.append(event.delta_us)
+
+
+b["events"].open_perf_buffer(callback, struct_name="latency_event")
+
+print("Tracing vfs_read latency... Hit Ctrl-C to end.")
+
+try:
+    while True:
+        b["events"].poll(1000)
+        if len(latencies) > 0 and len(latencies) % 1000 == 0:
+            print(f"Collected {len(latencies)} samples...")
+
+except KeyboardInterrupt:
+    print(f"Collected {len(latencies)} samples. Generating histogram...")
+
+# Create histogram with matplotlib
+if latencies:
+    # Use log scale for better visualization
+    log_latencies = np.log2(latencies)
+
+    plt.figure(figsize=(12, 6))
+
+    # Plot 1: Linear histogram
+    plt.subplot(1, 2, 1)
+    plt.hist(latencies, bins=50, edgecolor="black", alpha=0.7)
+    plt.xlabel("Latency (microseconds)")
+    plt.ylabel("Count")
+    plt.title("VFS Read Latency Distribution (Linear)")
+    plt.grid(True, alpha=0.3)
+
+    # Plot 2: Log2 histogram (like BCC)
+    plt.subplot(1, 2, 2)
+    plt.hist(log_latencies, bins=50, edgecolor="black", alpha=0.7, color="orange")
+    plt.xlabel("log2(Latency in µs)")
+    plt.ylabel("Count")
+    plt.title("VFS Read Latency Distribution (Log2)")
+    plt.grid(True, alpha=0.3)
+
+    # Add statistics
+    print("Statistics:")
+    print(f"  Count:  {len(latencies)}")
+    print(f"  Min:    {min(latencies)} µs")
+    print(f"  Max:    {max(latencies)} µs")
+    print(f"  Mean:   {np.mean(latencies):.2f} µs")
+    print(f"  Median: {np.median(latencies):.2f} µs")
+    print(f"  P95:    {np.percentile(latencies, 95):.2f} µs")
+    print(f"  P99:    {np.percentile(latencies, 99):.2f} µs")
+
+    plt.tight_layout()
+    plt.savefig("vfs_read_latency.png", dpi=150)
+    print("Histogram saved to vfs_read_latency.png")
+    plt.show()
+else:
+    print("No samples collected!")