Kannan Muthukkaruppan kmuthukk

Co-Founder/Co-CEO @ YugaByte

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kmuthukk / ysql_load_to_table_with_index.py

Last active May 25, 2019 00:20

Sample python program to load to a table with a secondary index using YugaByte DB's postgres compatible SQL API

	import psycopg2;
	from multiprocessing.dummy import Pool as ThreadPool

	num_write_threads=2
	num_users=10000

	def create_table():
	conn = psycopg2.connect("host=localhost dbname=postgres user=postgres port=5433")
	conn.set_session(autocommit=True)
	cur = conn.cursor()

kmuthukk / ysql_join_example.py

Last active May 16, 2019 01:53

a parallel program to test simple join performance with YugaByte postgres-compatible YSQL API

	# Dependencies:
	# On CentOS you can install psycopg2 thus:
	#
	# sudo yum install postgresql-libs
	# sudo yum install python-psycopg2
	#

	import psycopg2
	import time
	import random

kmuthukk / ysql_serializable_isolation_demo.py

Last active April 29, 2019 01:25

Demo of Serializable Isolation in YugaByte DB: Concurrent Transactions That Flip Color of Items

	import psycopg2
	from threading import Thread,Semaphore
	from multiprocessing.dummy import Pool as ThreadPool

	#
	# The test uses the classic example of a set of black and white items to
	# illustrate the need, in some situations, for transaction support with
	# serializable isolation level.
	#
	# In this test two concurrent transactions- one that flips white colored

kmuthukk / ysql_parallel_writer_and_reader.py

Last active April 18, 2019 04:00

Sample python program that does parallel inserts into a user_actions table, then does both point reads and range reads against YugaByte DB's YSQL (postgres compatible API)

	import psycopg2;
	import time
	import random
	from multiprocessing.dummy import Pool as ThreadPool

	# Load Phase params
	num_write_threads=4
	num_users=500
	num_msgs=50
	table_name = "user_actions"

kmuthukk / ysql_parallel_inserts.py

Last active April 18, 2019 03:11

sample python program to do single row inserts in parallel for YugaByte DB's YSQL (postgres compatible API)

	import psycopg2;
	import time
	from multiprocessing.dummy import Pool as ThreadPool

	num_threads=8
	num_users=1000
	num_msgs=50
	table_name = "user_actions"

	def create_table():

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