add fig5

figure_8/figure8-join.py

@@ -83,7 +83,7 @@ usage_schema = StructType() \
     .add("cpu_usage_dist_98", DoubleType(), True) \
     .add("cpu_usage_dist_99", DoubleType(), True)
     
-dfu = spark.read.format("csv") \
+dfu = spark.read.format("json") \
     .option("header", False) \
     .schema(usage_schema) \
     .load(dfupath)

spatial_resource_waste/spatial_res_actual_csv.py

@@ -62,15 +62,16 @@ spark = pyspark.sql.SparkSession.builder \
     .appName("task_slowdown") \
     .config("spark.driver.maxResultSize", "256g") \
     .config("spark.local.dir", "/home/claudio/tmp") \
-    .config("spark.driver.memory", "120g") \
+    .config("spark.driver.memory", "200g") \
     .getOrCreate()
 sc = spark.sparkContext
 
-path = "/home/claudio/" + cluster + "/" + cluster
-path += "_instance_usage*.csv.gz"
+# path = "/home/claudio/" + cluster + "/" + cluster
+# path += "_instance_usage*.csv.gz"
+path = "/home/claudio/raid0/google_2019/instance_usage/" + cluster + "/" + cluster + "_instance_usage*.json.gz"
 #path += "_test.csv"
 
-df = spark.read.format("csv") \
+df = spark.read.format("json") \
     .option("header", False) \
     .schema(schema) \
     .load(path)

table_iii/fig5.py

@@ -0,0 +1,68 @@
+#!/usr/bin/env python3
+# coding: utf-8
+
+import json
+import pandas
+import findspark
+findspark.init()
+import pyspark
+import pyspark.sql
+import sys
+import gzip
+import os
+
+import pyspark.sql.functions as F
+from pyspark import AccumulatorParam
+from pyspark.sql.functions import lit
+from pyspark.sql import Window
+from pyspark.sql.types import StructType, LongType, StringType, ByteType
+
+def main():
+    global DIR
+    global NAME
+    global launched
+
+    if len(sys.argv) != 4:
+        print(sys.argv[0] + " {cluster} {tmpdir} {maxram}")
+        sys.exit()
+
+    cluster=sys.argv[1]
+    DIR = os.path.dirname(__file__)
+    NAME = "fig-5-" + cluster
+
+    if os.path.exists(DIR + "/" + NAME + "-working") or os.path.exists(DIR + "/" + NAME + ".parquet"):
+        print("already launched")
+        launched = True
+        sys.exit()
+
+    os.system("touch " + DIR + "/" + NAME + "-working")
+
+    spark = pyspark.sql.SparkSession.builder \
+      .appName(NAME) \
+      .config("spark.driver.maxResultSize", "32g") \
+      .config("spark.local.dir", sys.argv[2]) \
+      .config("spark.driver.memory", sys.argv[3]) \
+      .getOrCreate()
+    sc = spark.sparkContext
+
+    df = spark.read.parquet(DIR + "/bigtable-" + cluster + ".parquet")
+
+    cnt_cond = lambda cond: F.sum(F.when(cond, 1).otherwise(0))
+
+    df = df.groupBy(["count_4", "count_5", "count_7", "count_8"]).agg( \
+        cnt_cond(F.col('task_term') == 6).alias('count_succ'), 
+        cnt_cond(F.col('task_term') != 6).alias('count_not_succ'))
+
+    df.repartition(1).write.csv(DIR + "/" + NAME + ".csv")
+
+if __name__ == "__main__":
+    launched = False
+    DIR = None
+    NAME = None
+    try:
+        main()
+    finally:    
+        if not launched and DIR and NAME:
+            os.system("rm -v " + DIR + "/" + NAME + "-working")
+
+# vim: set ts=4 sw=4 et tw=120: