feat(pyspark): add read_csv, read_parquet, and register

ibis/backends/duckdb/__init__.py

@@ -187,9 +187,8 @@ def register(
             parquet/csv files, an iterable of parquet or CSV files, a pandas
             dataframe, a pyarrow table or dataset, or a postgres URI.
         table_name
-            An optional name to use for the created table. This defaults to the
-            filename if a path (with hyphens replaced with underscores), or
-            sequentially generated name otherwise.
+            An optional name to use for the created table. This defaults to a
+            sequentially generated name.
         **kwargs
             Additional keyword arguments passed to DuckDB loading functions for
             CSV or parquet.  See https://duckdb.org/docs/data/csv and

ibis/backends/pyspark/__init__.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import itertools
 from pathlib import Path
 from typing import TYPE_CHECKING, Any
 
@@ -13,6 +14,7 @@
 import ibis.expr.operations as ops
 import ibis.expr.schema as sch
 import ibis.expr.types as ir
+from ibis import util
 from ibis.backends.base.df.scope import Scope
 from ibis.backends.base.df.timecontext import canonicalize_context, localize_context
 from ibis.backends.base.sql import BaseSQLBackend
@@ -37,6 +39,16 @@
     'escape': '"',
 }
 
+pa_n = itertools.count(0)
+csv_n = itertools.count(0)
+
+
+def normalize_filenames(source_list):
+    # Promote to list
+    source_list = util.promote_list(source_list)
+
+    return list(map(util.normalize_filename, source_list))
+
 
 class _PySparkCursor:
     """Spark cursor.
@@ -574,3 +586,121 @@ def _clean_up_cached_table(self, op):
         assert t.is_cached
         t.unpersist()
         assert not t.is_cached
+
+    def read_parquet(
+        self,
+        source: str | Path,
+        table_name: str | None = None,
+        **kwargs: Any,
+    ) -> ir.Table:
+        """Register a parquet file as a table in the current database.
+
+        Parameters
+        ----------
+        source
+            The data source. May be a path to a file or directory of parquet files.
+        table_name
+            An optional name to use for the created table. This defaults to
+            a sequentially generated name.
+        kwargs
+            Additional keyword arguments passed to PySpark.
+            https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.DataFrameReader.parquet.html
+
+        Returns
+        -------
+        ir.Table
+            The just-registered table
+        """
+        source = util.normalize_filename(source)
+        spark_df = self._session.read.parquet(source, **kwargs)
+        table_name = table_name or f"ibis_read_parquet_{next(pa_n)}"
+
+        spark_df.createOrReplaceTempView(table_name)
+        return self.table(table_name)
+
+    def read_csv(
+        self,
+        source_list: str | list[str] | tuple[str],
+        table_name: str | None = None,
+        **kwargs: Any,
+    ) -> ir.Table:
+        """Register a CSV file as a table in the current database.
+
+        Parameters
+        ----------
+        source_list
+            The data source(s). May be a path to a file or directory of CSV files, or an
+            iterable of CSV files.
+        table_name
+            An optional name to use for the created table. This defaults to
+            a sequentially generated name.
+        kwargs
+            Additional keyword arguments passed to PySpark loading function.
+            https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.DataFrameReader.csv.html
+
+        Returns
+        -------
+        ir.Table
+            The just-registered table
+        """
+        source_list = normalize_filenames(source_list)
+        spark_df = self._session.read.csv(source_list, **kwargs)
+        table_name = table_name or f"ibis_read_csv_{next(csv_n)}"
+
+        spark_df.createOrReplaceTempView(table_name)
+        return self.table(table_name)
+
+    def register(
+        self,
+        source: str | Path | Any,
+        table_name: str | None = None,
+        **kwargs: Any,
+    ) -> ir.Table:
+        """Register a data source as a table in the current database.
+
+        Parameters
+        ----------
+        source
+            The data source(s). May be a path to a file or directory of
+            parquet/csv files, or an iterable of CSV files.
+        table_name
+            An optional name to use for the created table. This defaults to
+            a sequentially generated name.
+        **kwargs
+            Additional keyword arguments passed to PySpark loading functions for
+            CSV or parquet.
+
+        Returns
+        -------
+        ir.Table
+            The just-registered table
+        """
+
+        if isinstance(source, (str, Path)):
+            first = str(source)
+        elif isinstance(source, (list, tuple)):
+            first = source[0]
+        else:
+            self._register_failure()
+
+        if first.startswith(("parquet://", "parq://")) or first.endswith(
+            ("parq", "parquet")
+        ):
+            return self.read_parquet(source, table_name=table_name, **kwargs)
+        elif first.startswith(
+            ("csv://", "csv.gz://", "txt://", "txt.gz://")
+        ) or first.endswith(("csv", "csv.gz", "tsv", "tsv.gz", "txt", "txt.gz")):
+            return self.read_csv(source, table_name=table_name, **kwargs)
+        else:
+            self._register_failure()  # noqa: RET503
+
+    def _register_failure(self):
+        import inspect
+
+        msg = ", ".join(
+            name for name, _ in inspect.getmembers(self) if name.startswith("read_")
+        )
+        raise ValueError(
+            f"Cannot infer appropriate read function for input, "
+            f"please call one of {msg} directly"
+        )

ibis/backends/tests/test_register.py

@@ -41,7 +41,15 @@ def gzip_csv(data_directory, tmp_path):
     ("fname", "in_table_name", "out_table_name"),
     [
         param("diamonds.csv", None, "ibis_read_csv_", id="default"),
-        param("csv://diamonds.csv", "Diamonds2", "Diamonds2", id="csv_name"),
+        param(
+            "csv://diamonds.csv",
+            "Diamonds2",
+            "Diamonds2",
+            id="csv_name",
+            marks=pytest.mark.notyet(
+                ["pyspark"], reason="pyspark lowercases view names"
+            ),
+        ),
         param(
             "file://diamonds.csv",
             "fancy_stones",
@@ -53,11 +61,14 @@ def gzip_csv(data_directory, tmp_path):
             "fancy stones",
             "fancy stones",
             id="file_atypical_name",
+            marks=pytest.mark.notyet(
+                ["pyspark"], reason="no spaces allowed in view names"
+            ),
         ),
         param(
             ["file://diamonds.csv", "diamonds.csv"],
-            "fancy stones",
-            "fancy stones",
+            "fancy_stones2",
+            "fancy_stones2",
             id="multi_csv",
             marks=pytest.mark.notyet(
                 ["polars", "datafusion"],
@@ -76,7 +87,6 @@ def gzip_csv(data_directory, tmp_path):
         "mysql",
         "pandas",
         "postgres",
-        "pyspark",
         "snowflake",
         "sqlite",
         "trino",
@@ -102,7 +112,6 @@ def test_register_csv(con, data_directory, fname, in_table_name, out_table_name)
         "mysql",
         "pandas",
         "postgres",
-        "pyspark",
         "snowflake",
         "sqlite",
         "trino",
@@ -125,7 +134,6 @@ def test_register_csv_gz(con, data_directory, gzip_csv):
         "mysql",
         "pandas",
         "postgres",
-        "pyspark",
         "snowflake",
         "sqlite",
         "trino",
@@ -179,7 +187,6 @@ def read_table(path: Path) -> Iterator[tuple[str, pa.Table]]:
         "mysql",
         "pandas",
         "postgres",
-        "pyspark",
         "snowflake",
         "sqlite",
         "trino",
@@ -381,3 +388,90 @@ def test_register_garbage(con, monkeypatch):
 
     with pytest.raises(FileNotFoundError):
         con.read_parquet("garbage_notafile")
+
+
+@pytest.mark.parametrize(
+    ("fname", "in_table_name", "out_table_name"),
+    [
+        (
+            "functional_alltypes.parquet",
+            None,
+            "ibis_read_parquet",
+        ),
+        ("functional_alltypes.parquet", "funk_all", "funk_all"),
+    ],
+)
+@pytest.mark.notyet(
+    [
+        "bigquery",
+        "clickhouse",
+        "dask",
+        "impala",
+        "mssql",
+        "mysql",
+        "pandas",
+        "postgres",
+        "snowflake",
+        "sqlite",
+        "trino",
+    ]
+)
+def test_read_parquet(
+    con, tmp_path, data_directory, fname, in_table_name, out_table_name
+):
+    pq = pytest.importorskip("pyarrow.parquet")
+
+    fname = Path(fname)
+    table = read_table(data_directory / fname.name)
+
+    pq.write_table(table, tmp_path / fname.name)
+
+    with pushd(data_directory):
+        if con.name == "pyspark":
+            # pyspark doesn't respect CWD
+            fname = str(Path(fname).absolute())
+        table = con.read_parquet(fname, table_name=in_table_name)
+
+    assert any(t.startswith(out_table_name) for t in con.list_tables())
+
+    if con.name != "datafusion":
+        table.count().execute()
+
+
+@pytest.mark.parametrize(
+    ("fname", "in_table_name", "out_table_name"),
+    [
+        param("diamonds.csv", None, "ibis_read_csv_", id="default"),
+        param(
+            "diamonds.csv",
+            "fancy_stones",
+            "fancy_stones",
+            id="file_name",
+        ),
+    ],
+)
+@pytest.mark.notyet(
+    [
+        "bigquery",
+        "clickhouse",
+        "dask",
+        "impala",
+        "mssql",
+        "mysql",
+        "pandas",
+        "postgres",
+        "snowflake",
+        "sqlite",
+        "trino",
+    ]
+)
+def test_read_csv(con, data_directory, fname, in_table_name, out_table_name):
+    with pushd(data_directory):
+        if con.name == "pyspark":
+            # pyspark doesn't respect CWD
+            fname = str(Path(fname).absolute())
+        table = con.read_csv(fname, table_name=in_table_name)
+
+    assert any(t.startswith(out_table_name) for t in con.list_tables())
+    if con.name != "datafusion":
+        table.count().execute()