Deprecate --file-store CLI argument to mlflow server and mlflow ui (

mlflow#1196)

Removes the --file-store option from the mlflow server and mlflow ui CLI commands. Users should update their CLI commands to use the --backend-store-uri option instead. For example,
mlflow server --file-store /my/local/path becomes mlflow server --backend-store-uri file:///my/local/path

README.rst

@@ -45,9 +45,9 @@ Start it with::
     mlflow ui
 
 **Note:** Running ``mlflow ui`` from within a clone of MLflow is not recommended - doing so will
-run the dev UI from source. We recommend running the UI from a different working directory, using the
-``--file-store`` option to specify which log directory to run against. Alternatively, see instructions
-for running the dev UI in the `contributor guide <CONTRIBUTING.rst>`_.
+run the dev UI from source. We recommend running the UI from a different working directory,
+specifying a backend store via the ``--backend-store-uri`` option. Alternatively, see
+instructions for running the dev UI in the `contributor guide <CONTRIBUTING.rst>`_.
 
 
 Running a Project from a URI

docs/source/tracking.rst

@@ -275,8 +275,6 @@ By default ``--backend-store-uri`` is set to the local ``./mlruns`` directory (t
 running ``mlflow run`` locally), but when running a server, make sure that this points to a
 persistent (that is, non-ephemeral) file system location.
 
-.. note::
-  For backwards compatibility, ``--file-store`` is an alias for this option.
 
 The artifact store is a location suitable for large data (such as an S3 bucket or shared NFS
 file system) and is where clients log their artifact output (for example, models).

mlflow/R/mlflow/R/tracking-server.R

@@ -58,7 +58,7 @@ mlflow_server <- function(file_store = "mlruns", default_artifact_root = NULL,
   file_store <- fs::path_abs(file_store)
 
   args <- mlflow_cli_param(list(), "--port", port) %>%
-    mlflow_cli_param("--file-store", file_store) %>%
+    mlflow_cli_param("--backend-store-uri", file_store) %>%
     mlflow_cli_param("--default-artifact-root", default_artifact_root) %>%
     mlflow_cli_param("--host", host) %>%
     mlflow_cli_param("--port", port) %>%

mlflow/cli.py

@@ -144,12 +144,13 @@ def run(uri, entry_point, version, param_list, experiment_name, experiment_id, m
 
 
 @cli.command()
-@click.option("--backend-store-uri", "--file-store", metavar="PATH",
+@click.option("--backend-store-uri", metavar="PATH",
               default=DEFAULT_LOCAL_FILE_AND_ARTIFACT_PATH,
-              help="URI or path for backend store implementation. Acceptable backend store "
-                   "are SQLAlchemy compatible implementation or local storage. "
-                   "Example 'sqlite:///path/to/file.db'. "
-                   "By default file backed store will be used. (default: ./mlruns).")
+              help="URI to which to persist experiment and run data. Acceptable URIs are "
+                   "SQLAlchemy-compatible database connection strings "
+                   "(e.g. 'sqlite:///path/to/file.db') or local filesystem URIs "
+                   "(e.g. 'file:///absolute/path/to/directory'). By default, data will be logged "
+                   "to the ./mlruns directory.")
 @click.option("--default-artifact-root", metavar="URI", default=None,
               help="Path to local directory to store artifacts, for new experiments. "
                    "Note that this flag does not impact already-created experiments. "
@@ -201,14 +202,13 @@ def _validate_static_prefix(ctx, param, value):  # pylint: disable=unused-argume
 
 
 @cli.command()
-@click.option("--backend-store-uri", "--file-store", metavar="PATH",
+@click.option("--backend-store-uri", metavar="PATH",
               default=DEFAULT_LOCAL_FILE_AND_ARTIFACT_PATH,
-              help="URI or path for backend store implementation. Acceptable backend store "
-                   "are SQLAlchemy compatible implementation or local storage. Supports "
-                   "various SQLAlchemy compatible database like SQLite, MySQL, PostgreSQL. As an "
-                   "example MySQL backed store can be configured using connection string. "
-                   "'mysql://<user_name>:<password>@<host>:<port>/<database_name>' "
-                   "By default file based backed store will be used. (default: ./mlruns).")
+              help="URI to which to persist experiment and run data. Acceptable URIs are "
+                   "SQLAlchemy-compatible database connection strings "
+                   "(e.g. 'sqlite:///path/to/file.db') or local filesystem URIs "
+                   "(e.g. 'file:///absolute/path/to/directory'). By default, data will be logged "
+                   "to the ./mlruns directory.")
 @click.option("--default-artifact-root", metavar="URI", default=None,
               help="Local or S3 URI to store artifacts, for new experiments. "
                    "Note that this flag does not impact already-created experiments. "

mlflow/java/client/src/test/java/org/mlflow/tracking/TestClientProvider.java

@@ -84,7 +84,7 @@ private MlflowClient startServerProcess() throws IOException {
     int freePort = getFreePort();
     String bindAddress = "127.0.0.1";
     pb.command("mlflow", "server", "--host", bindAddress, "--port", "" + freePort,
-      "--file-store", tempDir.resolve("mlruns").toString(), "--workers", "1");
+      "--backend-store-uri", tempDir.resolve("mlruns").toString(), "--workers", "1");
     serverProcess = pb.start();
 
     // NB: We cannot use pb.inheritIO() because that interacts poorly with the Maven