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fix spark cluster start mechanism and add extra dev requirements #986
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -1,19 +1,27 @@ | ||
from multiprocessing import Lock | ||
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import time | ||
import pytest | ||
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_db_start_lock = Lock() | ||
_DB_CLUSTER_STARTED = False | ||
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def _wait_for_databricks_cluster(project): | ||
""" | ||
It takes roughly 3min for the cluster to start, to be safe we'll wait for 5min | ||
""" | ||
for _ in range(60): | ||
try: | ||
project.run_sql("SELECT 1", fetch=True) | ||
return | ||
except Exception: | ||
time.sleep(10) | ||
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raise Exception("Databricks cluster did not start in time") | ||
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# Running this should prevent tests from needing to be retried because the Databricks cluster isn't available | ||
@pytest.fixture(scope="class", autouse=True) | ||
def start_databricks_cluster(project, request): | ||
global _DB_CLUSTER_STARTED | ||
profile_type = request.config.getoption("--profile") | ||
with _db_start_lock: | ||
if "databricks" in profile_type and not _DB_CLUSTER_STARTED: | ||
print("Starting Databricks cluster") | ||
project.run_sql("SELECT 1") | ||
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_DB_CLUSTER_STARTED = True | ||
if "databricks" in profile_type: | ||
_wait_for_databricks_cluster(project) | ||
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yield 1 |
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Separating these out reduces the frequency of cache invalidation