Merge branch 'master' into add_tests

kafka/client.py contained duplicate copies of same refactor, merged.
Move test/test_integration.py changes into test/test_producer_integration.

Conflicts:
	kafka/client.py
	servers/0.8.0/kafka-src
	test/test_integration.py

Author: wizzat

kafka/producer.py

@@ -2,6 +2,7 @@
 
 import logging
 import time
+import random
 
 from Queue import Empty
 from collections import defaultdict
@@ -180,14 +181,20 @@ class SimpleProducer(Producer):
     batch_send - If True, messages are send in batches
     batch_send_every_n - If set, messages are send in batches of this size
     batch_send_every_t - If set, messages are send after this timeout
+    random_start - If true, randomize the initial partition which the
+                   the first message block will be published to, otherwise
+                   if false, the first message block will always publish 
+                   to partition 0 before cycling through each partition
     """
     def __init__(self, client, async=False,
                  req_acks=Producer.ACK_AFTER_LOCAL_WRITE,
                  ack_timeout=Producer.DEFAULT_ACK_TIMEOUT,
                  batch_send=False,
                  batch_send_every_n=BATCH_SEND_MSG_COUNT,
-                 batch_send_every_t=BATCH_SEND_DEFAULT_INTERVAL):
+                 batch_send_every_t=BATCH_SEND_DEFAULT_INTERVAL,
+                 random_start=False):
         self.partition_cycles = {}
+        self.random_start = random_start
         super(SimpleProducer, self).__init__(client, async, req_acks,
                                              ack_timeout, batch_send,
                                              batch_send_every_n,
@@ -198,6 +205,13 @@ def _next_partition(self, topic):
             if topic not in self.client.topic_partitions:
                 self.client.load_metadata_for_topics(topic)
             self.partition_cycles[topic] = cycle(self.client.topic_partitions[topic])
+
+            # Randomize the initial partition that is returned
+            if self.random_start:
+                num_partitions = len(self.client.topic_partitions[topic])
+                for _ in xrange(random.randint(0, num_partitions-1)):
+                    self.partition_cycles[topic].next()
+
         return self.partition_cycles[topic].next()
 
     def send_messages(self, topic, *msg):

test/test_producer_integration.py

@@ -124,29 +124,47 @@ def test_simple_producer(self):
         start_offset1 = self.current_offset(self.topic, 1)
         producer = SimpleProducer(self.client)
 
-        # Will go to partition 0
-        msg1, msg2, msg3, msg4, msg5 = [ str(uuid.uuid4()) for x in xrange(5)  ]
+        # Goes to first partition, randomly.
         resp = producer.send_messages(self.topic, self.msg("one"), self.msg("two"))
         self.assert_produce_response(resp, start_offset0)
 
-        # Will go to partition 1
+        # Goes to the next partition, randomly.
         resp = producer.send_messages(self.topic, self.msg("three"))
         self.assert_produce_response(resp, start_offset1)
 
         self.assert_fetch_offset(0, start_offset0, [ self.msg("one"), self.msg("two") ])
         self.assert_fetch_offset(1, start_offset1, [ self.msg("three") ])
 
-        # Will go to partition 0
+        # Goes back to the first partition because there's only two partitions
         resp = producer.send_messages(self.topic, self.msg("four"), self.msg("five"))
         self.assert_produce_response(resp, start_offset0+2)
         self.assert_fetch_offset(0, start_offset0, [ self.msg("one"), self.msg("two"), self.msg("four"), self.msg("five") ])
 
         producer.stop()
 
     @kafka_versions("all")
-    def test_round_robin_partitioner(self):
-        msg1, msg2, msg3, msg4 = [ str(uuid.uuid4()) for _ in range(4) ]
+    def test_producer_random_order(self):
+        producer = SimpleProducer(self.client, random_start = True)
+        resp1 = producer.send_messages(self.topic, self.msg("one"), self.msg("two"))
+        resp2 = producer.send_messages(self.topic, self.msg("three"))
+        resp3 = producer.send_messages(self.topic, self.msg("four"), self.msg("five"))
+
+        self.assertEqual(resp1[0].partition, resp3[0].partition)
+        self.assertNotEqual(resp1[0].partition, resp2[0].partition)
+
+    @kafka_versions("all")
+    def test_producer_ordered_start(self):
+        producer = SimpleProducer(self.client, random_start = False)
+        resp1 = producer.send_messages(self.topic, self.msg("one"), self.msg("two"))
+        resp2 = producer.send_messages(self.topic, self.msg("three"))
+        resp3 = producer.send_messages(self.topic, self.msg("four"), self.msg("five"))
 
+        self.assertEqual(resp1[0].partition, 0)
+        self.assertEqual(resp2[0].partition, 1)
+        self.assertEqual(resp3[0].partition, 0)
+
+    @kafka_versions("all")
+    def test_round_robin_partitioner(self):
         start_offset0 = self.current_offset(self.topic, 0)
         start_offset1 = self.current_offset(self.topic, 1)