benchmark: add ycsb-c-esque plot

betree/haura-benchmarks/haura-plots/haura_plots/__init__.py

@@ -14,6 +14,7 @@
 from . import util
 from . import metrics_plots
 from . import cache_plots
+from . import ycsb_plots
 
 def sort_by_o_id(key):
     """
@@ -274,6 +275,7 @@ def main():
         plot_object_distribution(path)
         metrics_plots.plot_system(path)
         cache_plots.plot_cache(data, path)
+        ycsb_plots.plot_c(path)
         #plot_filesystem_test()
 
 if __name__ == "__main__":

betree/haura-benchmarks/haura-plots/haura_plots/ycsb_plots.py

@@ -0,0 +1,23 @@
+import os
+import pandas as pd
+import matplotlib.pyplot as plt
+
+def plot_c(path):
+    if not os.path.exists(f"{path}/ycsb_c.csv"):
+        return
+
+    data = pd.read_csv(f"{path}/ycsb_c.csv");
+    fig, ax = plt.subplots()
+    # op / s
+    first = data["ops"][0] / (data["time_ns"][0] / 10**9)
+    second = data["ops"][1] / (data["time_ns"][1] / 10**9)
+    if first < second / 2:
+        first = second / 2
+    optimal_scaling = [x * first for x in data["threads"]]
+    ax.plot(data["threads"], optimal_scaling, linestyle=":", label="Optimal", color='grey')
+    ax.bar(data["threads"], data["ops"] / (data["time_ns"] / 10**9))
+    ax.set_ylabel("Throughput [op/s]")
+    ax.set_title("YCSB-C Scaling Behavior")
+    ax.set_xlabel("Threads [#]")
+    fig.legend()
+    fig.savefig(f"{path}/ycsb_c.svg")

betree/haura-benchmarks/src/ycsb.rs

@@ -76,8 +76,9 @@ pub fn c(mut client: KvClient, size: u64, threads: usize, runtime: u64) {
             total += t.join().unwrap();
         }
         let end = start.elapsed();
-        w.write_fmt(format_args!("{workers},{total},{}", end.as_nanos()))
+        w.write_fmt(format_args!("{workers},{total},{}\n", end.as_nanos()))
             .unwrap();
+        w.flush().unwrap();
         println!("Achieved: {} ops/sec", total as f32 / end.as_secs_f32());
         println!("          {} ns avg", end.as_nanos() / total);
     }