Initial commit

mysql-insert.py

@@ -0,0 +1,53 @@
+#!/usr/bin/python3
+
+import time
+import MySQLdb
+
+############
+LOW_ROWS = 500
+HIGH_ROWS = 1000
+SAMPLES = 100
+############
+
+
+MICROSECONDS_PER_SECOND = 1000000
+
+db = MySQLdb.connect(host='35.235.123.231', user='root', password='foobar', db='benchmark')
+c = db.cursor()
+
+c.execute('DROP TABLE IF EXISTS pushrows')
+c.execute('''
+CREATE TABLE pushrows (
+    id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY
+) ENGINE=InnoDB
+''')
+
+c.execute('DROP PROCEDURE IF EXISTS pushrows')
+c.execute('''
+CREATE PROCEDURE pushrows (IN num INT)
+BEGIN
+	DECLARE x INT;
+	SET x = 0;
+	WHILE x < num DO
+                INSERT INTO pushrows VALUES ();
+		SET X = x + 1;
+	END WHILE;
+END
+''')
+
+def MeanExecutionTime(rows, samples):
+    start = time.perf_counter()
+    for _ in range(samples):
+        c.execute('CALL pushrows(%d)' % rows)
+    end = time.perf_counter()
+
+    return (end - start) / samples
+
+low = MeanExecutionTime(LOW_ROWS, SAMPLES)
+high = MeanExecutionTime(HIGH_ROWS, SAMPLES)
+
+per_row = (high - low) / (HIGH_ROWS - LOW_ROWS)
+base = high - (HIGH_ROWS * per_row)
+
+print('%dus/row' % (per_row * MICROSECONDS_PER_SECOND))
+print('%dus commit' % (base * MICROSECONDS_PER_SECOND))

mysql-network-latency-private.py

@@ -0,0 +1,24 @@
+#!/usr/bin/python3
+
+import time
+import MySQLdb
+
+############
+SAMPLES = 10000
+############
+
+
+MICROSECONDS_PER_SECOND = 1000000
+
+db = MySQLdb.connect(host='10.108.0.4', user='root', password='foobar')
+c = db.cursor()
+
+def MeanExecutionTime(samples):
+    start = time.perf_counter()
+    for _ in range(samples):
+        c.execute('SELECT 1')
+    end = time.perf_counter()
+
+    return (end - start) / samples
+
+print('%dus' % (MeanExecutionTime(SAMPLES) * MICROSECONDS_PER_SECOND))

mysql-network-latency-public.py

@@ -0,0 +1,24 @@
+#!/usr/bin/python3
+
+import time
+import MySQLdb
+
+############
+SAMPLES = 10000
+############
+
+
+MICROSECONDS_PER_SECOND = 1000000
+
+db = MySQLdb.connect(host='35.235.123.231', user='root', password='foobar', db='benchmark')
+c = db.cursor()
+
+def MeanExecutionTime(samples):
+    start = time.perf_counter()
+    for _ in range(samples):
+        c.execute('SELECT 1')
+    end = time.perf_counter()
+
+    return (end - start) / samples
+
+print('%dus' % (MeanExecutionTime(SAMPLES) * MICROSECONDS_PER_SECOND))

mysql-single-row-select.py

@@ -0,0 +1,50 @@
+#!/usr/bin/python3
+
+import time
+import MySQLdb
+
+############
+LOW_ROWS = 500
+HIGH_ROWS = 1000
+SAMPLES = 100
+############
+
+
+MICROSECONDS_PER_SECOND = 1000000
+
+db = MySQLdb.connect(host='35.235.123.231', user='root', password='foobar', db='benchmark')
+c = db.cursor()
+
+c.execute('DROP TABLE IF EXISTS pullrows')
+c.execute('''
+CREATE TABLE pullrows (
+    id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY
+) ENGINE=InnoDB
+''')
+c.execute('INSERT INTO pullrows VALUES (1)')
+
+c.execute('DROP PROCEDURE IF EXISTS pullrows')
+c.execute('''
+CREATE PROCEDURE pullrows (IN num INT)
+BEGIN
+	DECLARE x INT;
+	SET x = 0;
+	WHILE x < num DO
+                SELECT * FROM pullrows WHERE id=1;
+		SET X = x + 1;
+	END WHILE;
+END
+''')
+
+def MeanExecutionTime(rows, samples):
+    start = time.perf_counter()
+    for _ in range(samples):
+        c.execute('CALL pullrows(%d)' % rows)
+    end = time.perf_counter()
+
+    return (end - start) / samples
+
+diff = MeanExecutionTime(HIGH_ROWS, SAMPLES) - MeanExecutionTime(LOW_ROWS, SAMPLES)
+per_row = diff / (HIGH_ROWS - LOW_ROWS)
+
+print('%dus/row' % (per_row * MICROSECONDS_PER_SECOND))

postgres-insert.py

@@ -0,0 +1,56 @@
+#!/usr/bin/python3
+
+import time
+import psycopg2
+
+############
+LOW_ROWS = 500
+HIGH_ROWS = 1000
+SAMPLES = 100
+############
+
+
+MICROSECONDS_PER_SECOND = 1000000
+
+db = psycopg2.connect('host=35.235.77.254 user=postgres password=foobar dbname=benchmark')
+c = db.cursor()
+
+c.execute('DROP TABLE IF EXISTS pushrows')
+c.execute('''
+CREATE TABLE pushrows (
+    id BIGSERIAL PRIMARY KEY
+)
+''')
+
+c.execute('DROP FUNCTION IF EXISTS pushrows (numrows INTEGER)')
+c.execute('''
+CREATE FUNCTION pushrows (numrows INTEGER) RETURNS void AS $$
+DECLARE
+	rec RECORD;
+	x INTEGER := 0;
+BEGIN
+	LOOP
+		EXIT WHEN x = numrows;
+		x := x + 1;
+                INSERT INTO pushrows VALUES (DEFAULT);
+	END LOOP;
+END
+$$ language plpgsql
+''')
+
+def MeanExecutionTime(rows, samples):
+    start = time.perf_counter()
+    for _ in range(samples):
+        c.execute('SELECT pushrows(%d)' % rows)
+    end = time.perf_counter()
+
+    return (end - start) / samples
+
+low = MeanExecutionTime(LOW_ROWS, SAMPLES)
+high = MeanExecutionTime(HIGH_ROWS, SAMPLES)
+
+per_row = (high - low) / (HIGH_ROWS - LOW_ROWS)
+base = high - (HIGH_ROWS * per_row)
+
+print('%dus/row' % (per_row * MICROSECONDS_PER_SECOND))
+print('%dus commit' % (base * MICROSECONDS_PER_SECOND))

postgres-network-latency-private.py

@@ -0,0 +1,24 @@
+#!/usr/bin/python3
+
+import time
+import psycopg2
+
+############
+SAMPLES = 10000
+############
+
+
+MICROSECONDS_PER_SECOND = 1000000
+
+db = psycopg2.connect('host=10.108.1.3 user=postgres password=foobar')
+c = db.cursor()
+
+def MeanExecutionTime(samples):
+    start = time.perf_counter()
+    for _ in range(samples):
+        c.execute('SELECT 1')
+    end = time.perf_counter()
+
+    return (end - start) / samples
+
+print('%dus' % (MeanExecutionTime(SAMPLES) * MICROSECONDS_PER_SECOND))

postgres-network-latency-public.py

@@ -0,0 +1,24 @@
+#!/usr/bin/python3
+
+import time
+import psycopg2
+
+############
+SAMPLES = 10000
+############
+
+
+MICROSECONDS_PER_SECOND = 1000000
+
+db = psycopg2.connect('host=35.235.77.254 user=postgres password=foobar dbname=benchmark')
+c = db.cursor()
+
+def MeanExecutionTime(samples):
+    start = time.perf_counter()
+    for _ in range(samples):
+        c.execute('SELECT 1')
+    end = time.perf_counter()
+
+    return (end - start) / samples
+
+print('%dus' % (MeanExecutionTime(SAMPLES) * MICROSECONDS_PER_SECOND))

postgres-single-row-select.py

@@ -0,0 +1,54 @@
+#!/usr/bin/python3
+
+import time
+import psycopg2
+
+############
+LOW_ROWS = 500
+HIGH_ROWS = 1000
+SAMPLES = 100
+############
+
+
+MICROSECONDS_PER_SECOND = 1000000
+
+db = psycopg2.connect('host=35.235.77.254 user=postgres password=foobar dbname=benchmark')
+c = db.cursor()
+
+c.execute('DROP TABLE IF EXISTS pullrows')
+c.execute('''
+CREATE TABLE pullrows (
+    id BIGSERIAL PRIMARY KEY
+)
+''')
+c.execute('INSERT INTO pullrows VALUES (1)')
+
+c.execute('DROP FUNCTION IF EXISTS pullrows (numrows INTEGER)')
+c.execute('''
+CREATE FUNCTION pullrows (numrows INTEGER) RETURNS SETOF RECORD AS $$
+DECLARE
+	rec RECORD;
+	x INTEGER := 0;
+BEGIN
+	LOOP
+		EXIT WHEN x = numrows;
+		x := x + 1;
+		SELECT * FROM pullrows WHERE id=1 INTO rec;
+		RETURN NEXT rec;
+	END LOOP;
+END
+$$ language plpgsql
+''')
+
+def MeanExecutionTime(rows, samples):
+    start = time.perf_counter()
+    for _ in range(samples):
+        c.execute('SELECT * FROM pullrows(%d) AS (id BIGINT)' % rows)
+    end = time.perf_counter()
+
+    return (end - start) / samples
+
+diff = MeanExecutionTime(HIGH_ROWS, SAMPLES) - MeanExecutionTime(LOW_ROWS, SAMPLES)
+per_row = diff / (HIGH_ROWS - LOW_ROWS)
+
+print('%dus/row' % (per_row * MICROSECONDS_PER_SECOND))