diff --git a/python/ray/tune/trial.py b/python/ray/tune/trial.py
index 30ceb4a43..a3621454f 100644
--- a/python/ray/tune/trial.py
+++ b/python/ray/tune/trial.py
@@ -17,6 +17,7 @@ from ray.tune.result import TrainingResult, DEFAULT_RESULTS_DIR, pretty_print
 from ray.utils import random_string, binary_to_hex
 
 DEBUG_PRINT_INTERVAL = 5
+MAX_LEN_IDENTIFIER = 130
 
 
 class Resources(
@@ -337,6 +338,11 @@ class Trial(object):
             logger_creator=logger_creator)
 
     def __str__(self):
+        """Combines ``env`` with ``trainable_name`` and ``experiment_tag``.
+
+        Truncates to MAX_LEN_IDENTIFIER (default is 130) to avoid problems
+        when creating logging directories.
+        """
         if "env" in self.config:
             identifier = "{}_{}".format(
                 self.trainable_name, self.config["env"])
@@ -344,4 +350,4 @@ class Trial(object):
             identifier = self.trainable_name
         if self.experiment_tag:
             identifier += "_" + self.experiment_tag
-        return identifier
+        return identifier[:MAX_LEN_IDENTIFIER]
diff --git a/python/ray/tune/variant_generator.py b/python/ray/tune/variant_generator.py
index e6ea15fe6..bf80ddc9a 100644
--- a/python/ray/tune/variant_generator.py
+++ b/python/ray/tune/variant_generator.py
@@ -128,10 +128,17 @@ def _format_vars(resolved_vars):
                 last_string = False
                 pieces.append(k)
         pieces.reverse()
-        out.append("_".join(pieces) + "=" + str(value))
+        out.append("_".join(pieces) + "=" + _clean_value(value))
     return ",".join(out)
 
 
+def _clean_value(value):
+    if isinstance(value, float):
+        return "{:.5}".format(value)
+    else:
+        return str(value)
+
+
 def _generate_variants(spec):
     spec = copy.deepcopy(spec)
     unresolved = _unresolved_values(spec)
diff --git a/test/trial_runner_test.py b/test/trial_runner_test.py
index 88ff10167..f4e0762b2 100644
--- a/test/trial_runner_test.py
+++ b/test/trial_runner_test.py
@@ -13,7 +13,7 @@ from ray.tune import Trainable, TuneError
 from ray.tune import register_env, register_trainable, run_experiments
 from ray.tune.registry import _default_registry, TRAINABLE_CLASS
 from ray.tune.result import DEFAULT_RESULTS_DIR
-from ray.tune.trial import Trial, Resources
+from ray.tune.trial import Trial, Resources, MAX_LEN_IDENTIFIER
 from ray.tune.trial_runner import TrialRunner
 from ray.tune.variant_generator import generate_trials, grid_search, \
     RecursiveDependencyError
@@ -78,6 +78,19 @@ class TrainableFunctionApiTest(unittest.TestCase):
             "config": {"a": "b"},
         }})
 
+    def testLongFilename(self):
+        def train(config, reporter):
+            assert "/tmp/logdir/foo" in os.getcwd(), os.getcwd()
+            reporter(timesteps_total=1)
+        register_trainable("f1", train)
+        run_experiments({"foo": {
+            "run": "f1",
+            "local_dir": "/tmp/logdir",
+            "config": {
+                "a" * 50: lambda spec: 5.0 / 7,
+                "b" * 50: lambda spec: "long" * 40},
+        }})
+
     def testBadParams(self):
         def f():
             run_experiments({"foo": {}})
@@ -334,6 +347,26 @@ class TrialRunnerTest(unittest.TestCase):
         trial.stop(error=True)
         self.assertEqual(trial.status, Trial.ERROR)
 
+    def testExperimentTagTruncation(self):
+        ray.init()
+
+        def train(config, reporter):
+            reporter(timesteps_total=1)
+
+        register_trainable("f1", train)
+
+        experiments = {"foo": {
+            "run": "f1",
+            "config": {
+                "a" * 50: lambda spec: 5.0 / 7,
+                "b" * 50: lambda spec: "long" * 40},
+        }}
+
+        for name, spec in experiments.items():
+            for trial in generate_trials(spec, name):
+                self.assertLessEqual(
+                    len(str(trial)), MAX_LEN_IDENTIFIER)
+
     def testTrialErrorOnStart(self):
         ray.init()
         _default_registry.register(TRAINABLE_CLASS, "asdf", None)