From 08488c175f2e8532cb6aab84da2abd9ad57179cc Mon Sep 17 00:00:00 2001 From: Davies Liu Date: Mon, 9 Feb 2015 20:49:22 -0800 Subject: [SPARK-5469] restructure pyspark.sql into multiple files All the DataTypes moved into pyspark.sql.types The changes can be tracked by `--find-copies-harder -M25` ``` davieslocalhost:~/work/spark/python$ git diff --find-copies-harder -M25 --numstat master.. 2 5 python/docs/pyspark.ml.rst 0 3 python/docs/pyspark.mllib.rst 10 2 python/docs/pyspark.sql.rst 1 1 python/pyspark/mllib/linalg.py 21 14 python/pyspark/{mllib => sql}/__init__.py 14 2108 python/pyspark/{sql.py => sql/context.py} 10 1772 python/pyspark/{sql.py => sql/dataframe.py} 7 6 python/pyspark/{sql_tests.py => sql/tests.py} 8 1465 python/pyspark/{sql.py => sql/types.py} 4 2 python/run-tests 1 1 sql/core/src/main/scala/org/apache/spark/sql/test/ExamplePointUDT.scala ``` Also `git blame -C -C python/pyspark/sql/context.py` to track the history. Author: Davies Liu Closes #4479 from davies/sql and squashes the following commits: 1b5f0a5 [Davies Liu] Merge branch 'master' of github.com:apache/spark into sql 2b2b983 [Davies Liu] restructure pyspark.sql --- python/pyspark/sql/tests.py | 300 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 300 insertions(+) create mode 100644 python/pyspark/sql/tests.py (limited to 'python/pyspark/sql/tests.py') diff --git a/python/pyspark/sql/tests.py b/python/pyspark/sql/tests.py new file mode 100644 index 0000000000..d25c6365ed --- /dev/null +++ b/python/pyspark/sql/tests.py @@ -0,0 +1,300 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +""" +Unit tests for pyspark.sql; additional tests are implemented as doctests in +individual modules. +""" +import os +import sys +import pydoc +import shutil +import tempfile + +if sys.version_info[:2] <= (2, 6): + try: + import unittest2 as unittest + except ImportError: + sys.stderr.write('Please install unittest2 to test with Python 2.6 or earlier') + sys.exit(1) +else: + import unittest + + +from pyspark.sql import SQLContext, Column +from pyspark.sql.types import IntegerType, Row, ArrayType, StructType, StructField, \ + UserDefinedType, DoubleType, LongType +from pyspark.tests import ReusedPySparkTestCase + + +class ExamplePointUDT(UserDefinedType): + """ + User-defined type (UDT) for ExamplePoint. + """ + + @classmethod + def sqlType(self): + return ArrayType(DoubleType(), False) + + @classmethod + def module(cls): + return 'pyspark.tests' + + @classmethod + def scalaUDT(cls): + return 'org.apache.spark.sql.test.ExamplePointUDT' + + def serialize(self, obj): + return [obj.x, obj.y] + + def deserialize(self, datum): + return ExamplePoint(datum[0], datum[1]) + + +class ExamplePoint: + """ + An example class to demonstrate UDT in Scala, Java, and Python. + """ + + __UDT__ = ExamplePointUDT() + + def __init__(self, x, y): + self.x = x + self.y = y + + def __repr__(self): + return "ExamplePoint(%s,%s)" % (self.x, self.y) + + def __str__(self): + return "(%s,%s)" % (self.x, self.y) + + def __eq__(self, other): + return isinstance(other, ExamplePoint) and \ + other.x == self.x and other.y == self.y + + +class SQLTests(ReusedPySparkTestCase): + + @classmethod + def setUpClass(cls): + ReusedPySparkTestCase.setUpClass() + cls.tempdir = tempfile.NamedTemporaryFile(delete=False) + os.unlink(cls.tempdir.name) + cls.sqlCtx = SQLContext(cls.sc) + cls.testData = [Row(key=i, value=str(i)) for i in range(100)] + rdd = cls.sc.parallelize(cls.testData) + cls.df = cls.sqlCtx.inferSchema(rdd) + + @classmethod + def tearDownClass(cls): + ReusedPySparkTestCase.tearDownClass() + shutil.rmtree(cls.tempdir.name, ignore_errors=True) + + def test_udf(self): + self.sqlCtx.registerFunction("twoArgs", lambda x, y: len(x) + y, IntegerType()) + [row] = self.sqlCtx.sql("SELECT twoArgs('test', 1)").collect() + self.assertEqual(row[0], 5) + + def test_udf2(self): + self.sqlCtx.registerFunction("strlen", lambda string: len(string), IntegerType()) + self.sqlCtx.inferSchema(self.sc.parallelize([Row(a="test")])).registerTempTable("test") + [res] = self.sqlCtx.sql("SELECT strlen(a) FROM test WHERE strlen(a) > 1").collect() + self.assertEqual(4, res[0]) + + def test_udf_with_array_type(self): + d = [Row(l=range(3), d={"key": range(5)})] + rdd = self.sc.parallelize(d) + self.sqlCtx.inferSchema(rdd).registerTempTable("test") + self.sqlCtx.registerFunction("copylist", lambda l: list(l), ArrayType(IntegerType())) + self.sqlCtx.registerFunction("maplen", lambda d: len(d), IntegerType()) + [(l1, l2)] = self.sqlCtx.sql("select copylist(l), maplen(d) from test").collect() + self.assertEqual(range(3), l1) + self.assertEqual(1, l2) + + def test_broadcast_in_udf(self): + bar = {"a": "aa", "b": "bb", "c": "abc"} + foo = self.sc.broadcast(bar) + self.sqlCtx.registerFunction("MYUDF", lambda x: foo.value[x] if x else '') + [res] = self.sqlCtx.sql("SELECT MYUDF('c')").collect() + self.assertEqual("abc", res[0]) + [res] = self.sqlCtx.sql("SELECT MYUDF('')").collect() + self.assertEqual("", res[0]) + + def test_basic_functions(self): + rdd = self.sc.parallelize(['{"foo":"bar"}', '{"foo":"baz"}']) + df = self.sqlCtx.jsonRDD(rdd) + df.count() + df.collect() + df.schema() + + # cache and checkpoint + self.assertFalse(df.is_cached) + df.persist() + df.unpersist() + df.cache() + self.assertTrue(df.is_cached) + self.assertEqual(2, df.count()) + + df.registerTempTable("temp") + df = self.sqlCtx.sql("select foo from temp") + df.count() + df.collect() + + def test_apply_schema_to_row(self): + df = self.sqlCtx.jsonRDD(self.sc.parallelize(["""{"a":2}"""])) + df2 = self.sqlCtx.applySchema(df.map(lambda x: x), df.schema()) + self.assertEqual(df.collect(), df2.collect()) + + rdd = self.sc.parallelize(range(10)).map(lambda x: Row(a=x)) + df3 = self.sqlCtx.applySchema(rdd, df.schema()) + self.assertEqual(10, df3.count()) + + def test_serialize_nested_array_and_map(self): + d = [Row(l=[Row(a=1, b='s')], d={"key": Row(c=1.0, d="2")})] + rdd = self.sc.parallelize(d) + df = self.sqlCtx.inferSchema(rdd) + row = df.head() + self.assertEqual(1, len(row.l)) + self.assertEqual(1, row.l[0].a) + self.assertEqual("2", row.d["key"].d) + + l = df.map(lambda x: x.l).first() + self.assertEqual(1, len(l)) + self.assertEqual('s', l[0].b) + + d = df.map(lambda x: x.d).first() + self.assertEqual(1, len(d)) + self.assertEqual(1.0, d["key"].c) + + row = df.map(lambda x: x.d["key"]).first() + self.assertEqual(1.0, row.c) + self.assertEqual("2", row.d) + + def test_infer_schema(self): + d = [Row(l=[], d={}), + Row(l=[Row(a=1, b='s')], d={"key": Row(c=1.0, d="2")}, s="")] + rdd = self.sc.parallelize(d) + df = self.sqlCtx.inferSchema(rdd) + self.assertEqual([], df.map(lambda r: r.l).first()) + self.assertEqual([None, ""], df.map(lambda r: r.s).collect()) + df.registerTempTable("test") + result = self.sqlCtx.sql("SELECT l[0].a from test where d['key'].d = '2'") + self.assertEqual(1, result.head()[0]) + + df2 = self.sqlCtx.inferSchema(rdd, 1.0) + self.assertEqual(df.schema(), df2.schema()) + self.assertEqual({}, df2.map(lambda r: r.d).first()) + self.assertEqual([None, ""], df2.map(lambda r: r.s).collect()) + df2.registerTempTable("test2") + result = self.sqlCtx.sql("SELECT l[0].a from test2 where d['key'].d = '2'") + self.assertEqual(1, result.head()[0]) + + def test_struct_in_map(self): + d = [Row(m={Row(i=1): Row(s="")})] + rdd = self.sc.parallelize(d) + df = self.sqlCtx.inferSchema(rdd) + k, v = df.head().m.items()[0] + self.assertEqual(1, k.i) + self.assertEqual("", v.s) + + def test_convert_row_to_dict(self): + row = Row(l=[Row(a=1, b='s')], d={"key": Row(c=1.0, d="2")}) + self.assertEqual(1, row.asDict()['l'][0].a) + rdd = self.sc.parallelize([row]) + df = self.sqlCtx.inferSchema(rdd) + df.registerTempTable("test") + row = self.sqlCtx.sql("select l, d from test").head() + self.assertEqual(1, row.asDict()["l"][0].a) + self.assertEqual(1.0, row.asDict()['d']['key'].c) + + def test_infer_schema_with_udt(self): + from pyspark.sql.tests import ExamplePoint, ExamplePointUDT + row = Row(label=1.0, point=ExamplePoint(1.0, 2.0)) + rdd = self.sc.parallelize([row]) + df = self.sqlCtx.inferSchema(rdd) + schema = df.schema() + field = [f for f in schema.fields if f.name == "point"][0] + self.assertEqual(type(field.dataType), ExamplePointUDT) + df.registerTempTable("labeled_point") + point = self.sqlCtx.sql("SELECT point FROM labeled_point").head().point + self.assertEqual(point, ExamplePoint(1.0, 2.0)) + + def test_apply_schema_with_udt(self): + from pyspark.sql.tests import ExamplePoint, ExamplePointUDT + row = (1.0, ExamplePoint(1.0, 2.0)) + rdd = self.sc.parallelize([row]) + schema = StructType([StructField("label", DoubleType(), False), + StructField("point", ExamplePointUDT(), False)]) + df = self.sqlCtx.applySchema(rdd, schema) + point = df.head().point + self.assertEquals(point, ExamplePoint(1.0, 2.0)) + + def test_parquet_with_udt(self): + from pyspark.sql.tests import ExamplePoint + row = Row(label=1.0, point=ExamplePoint(1.0, 2.0)) + rdd = self.sc.parallelize([row]) + df0 = self.sqlCtx.inferSchema(rdd) + output_dir = os.path.join(self.tempdir.name, "labeled_point") + df0.saveAsParquetFile(output_dir) + df1 = self.sqlCtx.parquetFile(output_dir) + point = df1.head().point + self.assertEquals(point, ExamplePoint(1.0, 2.0)) + + def test_column_operators(self): + ci = self.df.key + cs = self.df.value + c = ci == cs + self.assertTrue(isinstance((- ci - 1 - 2) % 3 * 2.5 / 3.5, Column)) + rcc = (1 + ci), (1 - ci), (1 * ci), (1 / ci), (1 % ci) + self.assertTrue(all(isinstance(c, Column) for c in rcc)) + cb = [ci == 5, ci != 0, ci > 3, ci < 4, ci >= 0, ci <= 7, ci and cs, ci or cs] + self.assertTrue(all(isinstance(c, Column) for c in cb)) + cbool = (ci & ci), (ci | ci), (~ci) + self.assertTrue(all(isinstance(c, Column) for c in cbool)) + css = cs.like('a'), cs.rlike('a'), cs.asc(), cs.desc(), cs.startswith('a'), cs.endswith('a') + self.assertTrue(all(isinstance(c, Column) for c in css)) + self.assertTrue(isinstance(ci.cast(LongType()), Column)) + + def test_column_select(self): + df = self.df + self.assertEqual(self.testData, df.select("*").collect()) + self.assertEqual(self.testData, df.select(df.key, df.value).collect()) + self.assertEqual([Row(value='1')], df.where(df.key == 1).select(df.value).collect()) + + def test_aggregator(self): + df = self.df + g = df.groupBy() + self.assertEqual([99, 100], sorted(g.agg({'key': 'max', 'value': 'count'}).collect()[0])) + self.assertEqual([Row(**{"AVG(key#0)": 49.5})], g.mean().collect()) + + from pyspark.sql import Dsl + self.assertEqual((0, u'99'), tuple(g.agg(Dsl.first(df.key), Dsl.last(df.value)).first())) + self.assertTrue(95 < g.agg(Dsl.approxCountDistinct(df.key)).first()[0]) + self.assertEqual(100, g.agg(Dsl.countDistinct(df.value)).first()[0]) + + def test_help_command(self): + # Regression test for SPARK-5464 + rdd = self.sc.parallelize(['{"foo":"bar"}', '{"foo":"baz"}']) + df = self.sqlCtx.jsonRDD(rdd) + # render_doc() reproduces the help() exception without printing output + pydoc.render_doc(df) + pydoc.render_doc(df.foo) + pydoc.render_doc(df.take(1)) + + +if __name__ == "__main__": + unittest.main() -- cgit v1.2.3