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119723316e
It appears that newer versions of the gh runner require more memory. Some cases of the test test_rss_used_mem_gap allocate more than 6.5-7 gb of memory leaving barely 0.5gb to the gh runner (7.5 in total available) which sometimes cause the instance to run out of memory.
110 lines
4 KiB
Python
110 lines
4 KiB
Python
import pytest
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from redis import asyncio as aioredis
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from .utility import *
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import logging
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from . import dfly_args
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@pytest.mark.opt_only
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@pytest.mark.parametrize(
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"type, keys, val_size, elements",
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[
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("JSON", 200_000, 100, 100),
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("SET", 280_000, 100, 100),
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("HASH", 250_000, 100, 100),
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("ZSET", 250_000, 100, 100),
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("LIST", 300_000, 100, 100),
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("STRING", 3_500_000, 1000, 1),
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],
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)
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async def test_rss_used_mem_gap(df_factory, type, keys, val_size, elements):
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# Create a Dragonfly and fill it up with `type` until it reaches `min_rss`, then make sure that
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# the gap between used_memory and rss is no more than `max_unaccounted_ratio`.
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min_rss = 3 * 1024 * 1024 * 1024 # 3gb
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max_unaccounted = 200 * 1024 * 1024 # 200mb
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# We limit to 5gb just in case to sanity check the gh runner. Otherwise, if we ask for too much
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# memory it might force the gh runner to run out of memory (since OOM killer might not even
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# get a chance to run).
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df_server = df_factory.create(maxmemory="5gb")
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df_factory.start_all([df_server])
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client = df_server.client()
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await asyncio.sleep(1) # Wait for another RSS heartbeat update in Dragonfly
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cmd = f"DEBUG POPULATE {keys} {type} {val_size} RAND TYPE {type} ELEMENTS {elements}"
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print(f"Running {cmd}")
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await client.execute_command(cmd)
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await asyncio.sleep(2) # Wait for another RSS heartbeat update in Dragonfly
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info = await client.info("memory")
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logging.info(f'Used memory {info["used_memory"]}, rss {info["used_memory_rss"]}')
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assert info["used_memory"] > min_rss, "Weak testcase: too little used memory"
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delta = info["used_memory_rss"] - info["used_memory"]
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# It could be the case that the machine is configured to use swap if this assertion fails
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assert delta > 0
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assert delta < max_unaccounted
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delta = info["used_memory_rss"] - info["object_used_memory"]
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# TODO investigate why it fails on string
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if type == "json":
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assert delta > 0
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assert delta < max_unaccounted
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@pytest.mark.asyncio
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@dfly_args(
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{
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"maxmemory": "512mb",
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"proactor_threads": 2,
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"rss_oom_deny_ratio": 0.5,
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}
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)
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@pytest.mark.parametrize("admin_port", [0, 1112])
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async def test_rss_oom_ratio(df_factory, admin_port):
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"""
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Test dragonfly rejects denyoom commands and new connections when rss memory is above maxmemory*rss_oom_deny_ratio
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Test dragonfly does not rejects when rss memory goes below threshold
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"""
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df_server = df_factory.create(admin_port=admin_port)
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df_server.start()
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client = aioredis.Redis(port=df_server.port)
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await client.execute_command("DEBUG POPULATE 10000 key 40000 RAND")
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await asyncio.sleep(1) # Wait for another RSS heartbeat update in Dragonfly
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port = df_server.admin_port if admin_port else df_server.port
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new_client = aioredis.Redis(port=port)
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await new_client.ping()
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info = await new_client.info("memory")
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logging.debug(f'Used memory {info["used_memory"]}, rss {info["used_memory_rss"]}')
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reject_limit = 256 * 1024 * 1024 # 256mb
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assert info["used_memory_rss"] > reject_limit
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# get command from existing connection should not be rejected
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await client.execute_command("get x")
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# reject set due to oom
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with pytest.raises(redis.exceptions.ResponseError):
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await client.execute_command("set x y")
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if admin_port:
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# new client create should also fail if admin port was set
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client = aioredis.Redis(port=df_server.port)
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with pytest.raises(redis.exceptions.ConnectionError):
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await client.ping()
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# flush to free memory
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await new_client.flushall()
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await asyncio.sleep(2) # Wait for another RSS heartbeat update in Dragonfly
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info = await new_client.info("memory")
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logging.debug(f'Used memory {info["used_memory"]}, rss {info["used_memory_rss"]}')
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assert info["used_memory_rss"] < reject_limit
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# new client create shoud not fail after memory usage decrease
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client = aioredis.Redis(port=df_server.port)
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await client.execute_command("set x y")
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