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authorDavid Arthur <mumrah@gmail.com>2013-09-08 20:20:12 -0400
committerDavid Arthur <mumrah@gmail.com>2013-09-08 20:20:12 -0400
commit40d8e9e550b48755e2f40cfd0877a5b848a3254f (patch)
treee634245b6b0a52e40c9e03359413512feac252ed
parentc3bce13b845999483f7601836a2e7681dcd8ff10 (diff)
downloadkafka-python-40d8e9e550b48755e2f40cfd0877a5b848a3254f.tar.gz
Fixed #42, make fetch size configurable
Was hard coded to 1024 bytes which meant that larger messages were unconsumable since they would always get split causing the consumer to stop. It would probably be best to automatically retry truncated messages with a larger request size so you don't have to know your max message size ahead of time
-rw-r--r--kafka/consumer.py11
-rw-r--r--test/test_integration.py34
2 files changed, 41 insertions, 4 deletions
diff --git a/kafka/consumer.py b/kafka/consumer.py
index 4c64cf2..fbc9f94 100644
--- a/kafka/consumer.py
+++ b/kafka/consumer.py
@@ -206,6 +206,8 @@ class SimpleConsumer(Consumer):
auto_commit_every_t: default 5000. How much time (in milliseconds) to
wait before commit
+ fetch_size_bytes: number of bytes to request in a FetchRequest
+
Auto commit details:
If both auto_commit_every_n and auto_commit_every_t are set, they will
reset one another when one is triggered. These triggers simply call the
@@ -214,11 +216,12 @@ class SimpleConsumer(Consumer):
"""
def __init__(self, client, group, topic, auto_commit=True, partitions=None,
auto_commit_every_n=AUTO_COMMIT_MSG_COUNT,
- auto_commit_every_t=AUTO_COMMIT_INTERVAL):
+ auto_commit_every_t=AUTO_COMMIT_INTERVAL,
+ fetch_size_bytes=FETCH_MIN_BYTES):
self.partition_info = False # Do not return partition info in msgs
self.fetch_max_wait_time = FETCH_MAX_WAIT_TIME
- self.fetch_min_bytes = FETCH_MIN_BYTES
+ self.fetch_min_bytes = fetch_size_bytes
self.fetch_started = defaultdict(bool) # defaults to false
super(SimpleConsumer, self).__init__(client, group, topic,
@@ -243,6 +246,7 @@ class SimpleConsumer(Consumer):
1 is relative to the current offset
2 is relative to the latest known offset (tail)
"""
+
if whence == 1: # relative to current position
for partition, _offset in self.offsets.items():
self.offsets[partition] = _offset + offset
@@ -354,8 +358,7 @@ class SimpleConsumer(Consumer):
offset += 1
while True:
- # TODO: configure fetch size
- req = FetchRequest(self.topic, partition, offset, 1024)
+ req = FetchRequest(self.topic, partition, offset, self.fetch_min_bytes)
(resp,) = self.client.send_fetch_request([req],
max_wait_time=self.fetch_max_wait_time,
diff --git a/test/test_integration.py b/test/test_integration.py
index 3c524cf..6384b09 100644
--- a/test/test_integration.py
+++ b/test/test_integration.py
@@ -2,6 +2,8 @@ import logging
import unittest
import time
from datetime import datetime
+import string
+import random
from kafka import * # noqa
from kafka.common import * # noqa
@@ -738,6 +740,38 @@ class TestConsumer(unittest.TestCase):
consumer.stop()
+ def test_large_messages(self):
+ # Produce 10 "normal" size messages
+ messages1 = [create_message(random_string(1024)) for i in range(10)]
+ produce1 = ProduceRequest("test_large_messages", 0, messages1)
+
+ for resp in self.client.send_produce_request([produce1]):
+ self.assertEquals(resp.error, 0)
+ self.assertEquals(resp.offset, 0)
+
+ # Produce 10 messages that are too large (bigger than default fetch size)
+ messages2=[create_message(random_string(5000)) for i in range(10)]
+ produce2 = ProduceRequest("test_large_messages", 0, messages2)
+
+ for resp in self.client.send_produce_request([produce2]):
+ self.assertEquals(resp.error, 0)
+ self.assertEquals(resp.offset, 10)
+
+ consumer = SimpleConsumer(self.client, "group1", "test_large_messages")
+ it = consumer.__iter__()
+ for i in range(10):
+ self.assertEquals(messages1[i], it.next().message)
+
+ consumer = SimpleConsumer(self.client, "group2", "test_large_messages", fetch_size_bytes=5120)
+ it = consumer.__iter__()
+ for i in range(10):
+ self.assertEquals(messages1[i], it.next().message)
+ for i in range(10):
+ self.assertEquals(messages2[i], it.next().message)
+
+def random_string(l):
+ s = "".join(random.choice(string.printable) for i in xrange(l))
+ return s
if __name__ == "__main__":
logging.basicConfig(level=logging.DEBUG)