Skip ownership transfer test when using ray client to be compatible w…

…ith Ray 2.4.0 (#344) * skip ownership test when using ray client Signed-off-by: Zhi Lin <[email protected]> * test ray 2.4 Signed-off-by: Zhi Lin <[email protected]> * fix Signed-off-by: Zhi Lin <[email protected]> --------- Signed-off-by: Zhi Lin <[email protected]>
oap-project · May 26, 2023 · 9c094c4 · 9c094c4
1 parent e1753a2
commit 9c094c4
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Showing 4 changed files with 18 additions and 4 deletions.
diff --git a/.github/workflows/raydp.yml b/.github/workflows/raydp.yml
@@ -78,7 +78,7 @@ jobs:
  else
  pip install torch
  fi
- pip install pyarrow==6.0.1 ray[default]==2.1.0 pytest koalas tensorflow tabulate grpcio-tools wget
+ pip install pyarrow==6.0.1 ray[default]==2.4.0 pytest koalas tensorflow tabulate grpcio-tools wget
  pip install "xgboost_ray[default]<=0.1.13"
  pip install torchmetrics
  HOROVOD_WITH_GLOO=1

diff --git a/python/raydp/tests/test_data_owner_transfer.py b/python/raydp/tests/test_data_owner_transfer.py
@@ -39,10 +39,14 @@ def test_fail_without_data_ownership_transfer(ray_cluster):
  its owner (e.g. Spark JVM process) has terminated, which is expected.
  """
 
+ # skipping this to be compatible with ray 2.4.0
+ # see issue #343
+ if not ray.worker.global_worker.connected:
+ pytest.skip("Skip this test if using ray client")
+
  from raydp.spark.dataset import spark_dataframe_to_ray_dataset
-
- num_executor = 1
 
+ num_executor = 1
  spark = raydp.init_spark(
  app_name = "example",
  num_executors = num_executor,
@@ -84,6 +88,9 @@ def test_data_ownership_transfer(ray_cluster):
  This test should be able to execute till the end without crash as expected.
  """
 
+ if not ray.worker.global_worker.connected:
+ pytest.skip("Skip this test if using ray client")
+
  from raydp.spark.dataset import spark_dataframe_to_ray_dataset
  import numpy as np
 

diff --git a/python/raydp/tests/test_spark_cluster.py b/python/raydp/tests/test_spark_cluster.py
@@ -94,6 +94,10 @@ def test_spark_driver_and_executor_hostname(spark_on_ray_small):
 
 
 def test_ray_dataset_roundtrip(spark_on_ray_small):
+ # skipping this to be compatible with ray 2.4.0
+ # see issue #343
+ if not ray.worker.global_worker.connected:
+ pytest.skip("Skip this test if using ray client")
  spark = spark_on_ray_small
  spark_df = spark.createDataFrame([(1, "a"), (2, "b"), (3, "c")], ["one", "two"])
  rows = [(r.one, r.two) for r in spark_df.take(3)]
@@ -107,6 +111,10 @@ def test_ray_dataset_roundtrip(spark_on_ray_small):
 
 
 def test_ray_dataset_to_spark(spark_on_ray_small):
+ # skipping this to be compatible with ray 2.4.0
+ # see issue #343
+ if not ray.worker.global_worker.connected:
+ pytest.skip("Skip this test if using ray client")
  spark = spark_on_ray_small
  n = 5
  data = {"value": list(range(n))}

diff --git a/python/raydp/tf/estimator.py b/python/raydp/tf/estimator.py
@@ -171,7 +171,6 @@ def train_func(config):
  )
  if config["evaluate"]:
  eval_dataset = session.get_dataset_shard("evaluate")
- eval_dataset.fully_executed()
  eval_tf_dataset = eval_dataset.to_tf(
  feature_columns=config["feature_columns"],
  label_columns=config["label_columns"],