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| <h1>Source code for pyspark.sql.udtf</h1><div class="highlight"><pre> |
| <span></span><span class="c1">#</span> |
| <span class="c1"># Licensed to the Apache Software Foundation (ASF) under one or more</span> |
| <span class="c1"># contributor license agreements. See the NOTICE file distributed with</span> |
| <span class="c1"># this work for additional information regarding copyright ownership.</span> |
| <span class="c1"># The ASF licenses this file to You under the Apache License, Version 2.0</span> |
| <span class="c1"># (the "License"); you may not use this file except in compliance with</span> |
| <span class="c1"># the License. You may obtain a copy of the License at</span> |
| <span class="c1">#</span> |
| <span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span> |
| <span class="c1">#</span> |
| <span class="c1"># Unless required by applicable law or agreed to in writing, software</span> |
| <span class="c1"># distributed under the License is distributed on an "AS IS" BASIS,</span> |
| <span class="c1"># WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span> |
| <span class="c1"># See the License for the specific language governing permissions and</span> |
| <span class="c1"># limitations under the License.</span> |
| <span class="c1">#</span> |
| <span class="sd">"""</span> |
| <span class="sd">User-defined table function related classes and functions</span> |
| <span class="sd">"""</span> |
| <span class="kn">import</span> <span class="nn">pickle</span> |
| <span class="kn">from</span> <span class="nn">dataclasses</span> <span class="kn">import</span> <span class="n">dataclass</span><span class="p">,</span> <span class="n">field</span> |
| <span class="kn">import</span> <span class="nn">inspect</span> |
| <span class="kn">import</span> <span class="nn">sys</span> |
| <span class="kn">import</span> <span class="nn">warnings</span> |
| <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Type</span><span class="p">,</span> <span class="n">TYPE_CHECKING</span><span class="p">,</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Sequence</span><span class="p">,</span> <span class="n">Union</span> |
| |
| <span class="kn">from</span> <span class="nn">pyspark.errors</span> <span class="kn">import</span> <span class="n">PySparkAttributeError</span><span class="p">,</span> <span class="n">PySparkPicklingError</span><span class="p">,</span> <span class="n">PySparkTypeError</span> |
| <span class="kn">from</span> <span class="nn">pyspark.util</span> <span class="kn">import</span> <span class="n">PythonEvalType</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql.pandas.utils</span> <span class="kn">import</span> <span class="n">require_minimum_pandas_version</span><span class="p">,</span> <span class="n">require_minimum_pyarrow_version</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql.types</span> <span class="kn">import</span> <span class="n">DataType</span><span class="p">,</span> <span class="n">StructType</span><span class="p">,</span> <span class="n">_parse_datatype_string</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql.udf</span> <span class="kn">import</span> <span class="n">_wrap_function</span> |
| |
| <span class="k">if</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span> |
| <span class="kn">from</span> <span class="nn">py4j.java_gateway</span> <span class="kn">import</span> <span class="n">JavaObject</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql._typing</span> <span class="kn">import</span> <span class="n">ColumnOrName</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql.dataframe</span> <span class="kn">import</span> <span class="n">DataFrame</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql.session</span> <span class="kn">import</span> <span class="n">SparkSession</span> |
| |
| <span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span> |
| <span class="s2">"AnalyzeArgument"</span><span class="p">,</span> |
| <span class="s2">"AnalyzeResult"</span><span class="p">,</span> |
| <span class="s2">"PartitioningColumn"</span><span class="p">,</span> |
| <span class="s2">"OrderingColumn"</span><span class="p">,</span> |
| <span class="s2">"SelectedColumn"</span><span class="p">,</span> |
| <span class="s2">"SkipRestOfInputTableException"</span><span class="p">,</span> |
| <span class="s2">"UDTFRegistration"</span><span class="p">,</span> |
| <span class="p">]</span> |
| |
| |
| <span class="nd">@dataclass</span><span class="p">(</span><span class="n">frozen</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> |
| <span class="k">class</span> <span class="nc">AnalyzeArgument</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""</span> |
| <span class="sd"> The argument for Python UDTF's analyze static method.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> dataType : :class:`DataType`</span> |
| <span class="sd"> The argument's data type</span> |
| <span class="sd"> value : any, optional</span> |
| <span class="sd"> The calculated value if the argument is foldable; otherwise None</span> |
| <span class="sd"> isTable : bool</span> |
| <span class="sd"> If True, the argument is a table argument.</span> |
| <span class="sd"> isConstantExpression : bool</span> |
| <span class="sd"> If True, the argument is a constant-foldable scalar expression. Then the 'value' field</span> |
| <span class="sd"> contains None if the argument is a NULL literal, or a non-None value if the argument is a</span> |
| <span class="sd"> non-NULL literal. In this way, we can distinguish between a literal NULL argument and other</span> |
| <span class="sd"> types of arguments such as complex expression trees or table arguments where the 'value'</span> |
| <span class="sd"> field is always None.</span> |
| <span class="sd"> """</span> |
| |
| <span class="n">dataType</span><span class="p">:</span> <span class="n">DataType</span> |
| <span class="n">value</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Any</span><span class="p">]</span> |
| <span class="n">isTable</span><span class="p">:</span> <span class="nb">bool</span> |
| <span class="n">isConstantExpression</span><span class="p">:</span> <span class="nb">bool</span> |
| |
| |
| <span class="nd">@dataclass</span><span class="p">(</span><span class="n">frozen</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> |
| <span class="k">class</span> <span class="nc">PartitioningColumn</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""</span> |
| <span class="sd"> Represents an expression that the UDTF is specifying for Catalyst to partition the input table</span> |
| <span class="sd"> by. This can be either the name of a single column from the input table (such as "columnA"), or</span> |
| <span class="sd"> a SQL expression based on the column names of the input table (such as "columnA + columnB").</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> name : str</span> |
| <span class="sd"> The contents of the partitioning column name or expression represented as a SQL string.</span> |
| <span class="sd"> """</span> |
| |
| <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> |
| |
| |
| <span class="nd">@dataclass</span><span class="p">(</span><span class="n">frozen</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> |
| <span class="k">class</span> <span class="nc">OrderingColumn</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""</span> |
| <span class="sd"> Represents an expression that the UDTF is specifying for Catalyst to order the input partition</span> |
| <span class="sd"> by. This can be either the name of a single column from the input table (such as "columnA"),</span> |
| <span class="sd"> or a SQL expression based on the column names of the input table (such as "columnA + columnB").</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> name : str</span> |
| <span class="sd"> The contents of the ordering column name or expression represented as a SQL string.</span> |
| <span class="sd"> ascending : bool, default True</span> |
| <span class="sd"> This is if this expression specifies an ascending sorting order.</span> |
| <span class="sd"> overrideNullsFirst : str, optional</span> |
| <span class="sd"> If this is None, use the default behavior to sort NULL values first when sorting in</span> |
| <span class="sd"> ascending order, or last when sorting in descending order. Otherwise, if this is</span> |
| <span class="sd"> True or False, we override the default behavior accordingly.</span> |
| <span class="sd"> """</span> |
| |
| <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> |
| <span class="n">ascending</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span> |
| <span class="n">overrideNullsFirst</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span> |
| |
| |
| <span class="nd">@dataclass</span><span class="p">(</span><span class="n">frozen</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> |
| <span class="k">class</span> <span class="nc">SelectedColumn</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""</span> |
| <span class="sd"> Represents an expression that the UDTF is specifying for Catalyst to evaluate against the</span> |
| <span class="sd"> columns in the input TABLE argument. The UDTF then receives one input column for each expression</span> |
| <span class="sd"> in the list, in the order they are listed.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> name : str</span> |
| <span class="sd"> The contents of the selected column name or expression represented as a SQL string.</span> |
| <span class="sd"> alias : str, default ''</span> |
| <span class="sd"> If non-empty, this is the alias for the column or expression as visible from the UDTF's</span> |
| <span class="sd"> 'eval' method. This is required if the expression is not a simple column reference.</span> |
| <span class="sd"> """</span> |
| |
| <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> |
| <span class="n">alias</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">""</span> |
| |
| |
| <span class="c1"># Note: this class is a "dataclass" for purposes of convenience, but it is not marked "frozen"</span> |
| <span class="c1"># because the intention is that users may create subclasses of it for purposes of returning custom</span> |
| <span class="c1"># information from the "analyze" method.</span> |
| <span class="nd">@dataclass</span> |
| <span class="k">class</span> <span class="nc">AnalyzeResult</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""</span> |
| <span class="sd"> The return of Python UDTF's analyze static method.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> schema: :class:`StructType`</span> |
| <span class="sd"> The schema that the Python UDTF will return.</span> |
| <span class="sd"> withSinglePartition: bool</span> |
| <span class="sd"> If true, the UDTF is specifying for Catalyst to repartition all rows of the input TABLE</span> |
| <span class="sd"> argument to one collection for consumption by exactly one instance of the correpsonding</span> |
| <span class="sd"> UDTF class.</span> |
| <span class="sd"> partitionBy: sequence of :class:`PartitioningColumn`</span> |
| <span class="sd"> If non-empty, this is a sequence of expressions that the UDTF is specifying for Catalyst to</span> |
| <span class="sd"> partition the input TABLE argument by. In this case, calls to the UDTF may not include any</span> |
| <span class="sd"> explicit PARTITION BY clause, in which case Catalyst will return an error. This option is</span> |
| <span class="sd"> mutually exclusive with 'withSinglePartition'.</span> |
| <span class="sd"> orderBy: sequence of :class:`OrderingColumn`</span> |
| <span class="sd"> If non-empty, this is a sequence of expressions that the UDTF is specifying for Catalyst to</span> |
| <span class="sd"> sort the input TABLE argument by. Note that the 'partitionBy' list must also be non-empty</span> |
| <span class="sd"> in this case.</span> |
| <span class="sd"> select: sequence of :class:`SelectedColumn`</span> |
| <span class="sd"> If non-empty, this is a sequence of expressions that the UDTF is specifying for Catalyst to</span> |
| <span class="sd"> evaluate against the columns in the input TABLE argument. The UDTF then receives one input</span> |
| <span class="sd"> attribute for each name in the list, in the order they are listed.</span> |
| <span class="sd"> """</span> |
| |
| <span class="n">schema</span><span class="p">:</span> <span class="n">StructType</span> |
| <span class="n">withSinglePartition</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span> |
| <span class="n">partitionBy</span><span class="p">:</span> <span class="n">Sequence</span><span class="p">[</span><span class="n">PartitioningColumn</span><span class="p">]</span> <span class="o">=</span> <span class="n">field</span><span class="p">(</span><span class="n">default_factory</span><span class="o">=</span><span class="nb">tuple</span><span class="p">)</span> |
| <span class="n">orderBy</span><span class="p">:</span> <span class="n">Sequence</span><span class="p">[</span><span class="n">OrderingColumn</span><span class="p">]</span> <span class="o">=</span> <span class="n">field</span><span class="p">(</span><span class="n">default_factory</span><span class="o">=</span><span class="nb">tuple</span><span class="p">)</span> |
| <span class="n">select</span><span class="p">:</span> <span class="n">Sequence</span><span class="p">[</span><span class="n">SelectedColumn</span><span class="p">]</span> <span class="o">=</span> <span class="n">field</span><span class="p">(</span><span class="n">default_factory</span><span class="o">=</span><span class="nb">tuple</span><span class="p">)</span> |
| |
| |
| <span class="k">class</span> <span class="nc">SkipRestOfInputTableException</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""</span> |
| <span class="sd"> This represents an exception that the 'eval' method may raise to indicate that it is done</span> |
| <span class="sd"> consuming rows from the current partition of the input table. Then the UDTF's 'terminate'</span> |
| <span class="sd"> method runs (if any).</span> |
| <span class="sd"> """</span> |
| |
| <span class="k">pass</span> |
| |
| |
| <span class="k">def</span> <span class="nf">_create_udtf</span><span class="p">(</span> |
| <span class="bp">cls</span><span class="p">:</span> <span class="n">Type</span><span class="p">,</span> |
| <span class="n">returnType</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="n">StructType</span><span class="p">,</span> <span class="nb">str</span><span class="p">]],</span> |
| <span class="n">name</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> |
| <span class="n">evalType</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">PythonEvalType</span><span class="o">.</span><span class="n">SQL_TABLE_UDF</span><span class="p">,</span> |
| <span class="n">deterministic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> |
| <span class="p">)</span> <span class="o">-></span> <span class="s2">"UserDefinedTableFunction"</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""Create a Python UDTF with the given eval type."""</span> |
| <span class="n">udtf_obj</span> <span class="o">=</span> <span class="n">UserDefinedTableFunction</span><span class="p">(</span> |
| <span class="bp">cls</span><span class="p">,</span> <span class="n">returnType</span><span class="o">=</span><span class="n">returnType</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">evalType</span><span class="o">=</span><span class="n">evalType</span><span class="p">,</span> <span class="n">deterministic</span><span class="o">=</span><span class="n">deterministic</span> |
| <span class="p">)</span> |
| |
| <span class="k">return</span> <span class="n">udtf_obj</span> |
| |
| |
| <span class="k">def</span> <span class="nf">_create_py_udtf</span><span class="p">(</span> |
| <span class="bp">cls</span><span class="p">:</span> <span class="n">Type</span><span class="p">,</span> |
| <span class="n">returnType</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="n">StructType</span><span class="p">,</span> <span class="nb">str</span><span class="p">]],</span> |
| <span class="n">name</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> |
| <span class="n">deterministic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> |
| <span class="n">useArrow</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> |
| <span class="p">)</span> <span class="o">-></span> <span class="s2">"UserDefinedTableFunction"</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""Create a regular or an Arrow-optimized Python UDTF."""</span> |
| <span class="c1"># Determine whether to create Arrow-optimized UDTFs.</span> |
| <span class="k">if</span> <span class="n">useArrow</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">arrow_enabled</span> <span class="o">=</span> <span class="n">useArrow</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql</span> <span class="kn">import</span> <span class="n">SparkSession</span> |
| |
| <span class="n">session</span> <span class="o">=</span> <span class="n">SparkSession</span><span class="o">.</span><span class="n">_instantiatedSession</span> |
| <span class="n">arrow_enabled</span> <span class="o">=</span> <span class="kc">False</span> |
| <span class="k">if</span> <span class="n">session</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">value</span> <span class="o">=</span> <span class="n">session</span><span class="o">.</span><span class="n">conf</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"spark.sql.execution.pythonUDTF.arrow.enabled"</span><span class="p">)</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="ow">and</span> <span class="n">value</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span> <span class="o">==</span> <span class="s2">"true"</span><span class="p">:</span> |
| <span class="n">arrow_enabled</span> <span class="o">=</span> <span class="kc">True</span> |
| |
| <span class="n">eval_type</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">PythonEvalType</span><span class="o">.</span><span class="n">SQL_TABLE_UDF</span> |
| |
| <span class="k">if</span> <span class="n">arrow_enabled</span><span class="p">:</span> |
| <span class="c1"># Return the regular UDTF if the required dependencies are not satisfied.</span> |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">require_minimum_pandas_version</span><span class="p">()</span> |
| <span class="n">require_minimum_pyarrow_version</span><span class="p">()</span> |
| <span class="n">eval_type</span> <span class="o">=</span> <span class="n">PythonEvalType</span><span class="o">.</span><span class="n">SQL_ARROW_TABLE_UDF</span> |
| <span class="k">except</span> <span class="ne">ImportError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span> |
| <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span> |
| <span class="sa">f</span><span class="s2">"Arrow optimization for Python UDTFs cannot be enabled: </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">)</span><span class="si">}</span><span class="s2">. "</span> |
| <span class="sa">f</span><span class="s2">"Falling back to using regular Python UDTFs."</span><span class="p">,</span> |
| <span class="ne">UserWarning</span><span class="p">,</span> |
| <span class="p">)</span> |
| |
| <span class="k">return</span> <span class="n">_create_udtf</span><span class="p">(</span> |
| <span class="bp">cls</span><span class="o">=</span><span class="bp">cls</span><span class="p">,</span> |
| <span class="n">returnType</span><span class="o">=</span><span class="n">returnType</span><span class="p">,</span> |
| <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> |
| <span class="n">evalType</span><span class="o">=</span><span class="n">eval_type</span><span class="p">,</span> |
| <span class="n">deterministic</span><span class="o">=</span><span class="n">deterministic</span><span class="p">,</span> |
| <span class="p">)</span> |
| |
| |
| <span class="k">def</span> <span class="nf">_validate_udtf_handler</span><span class="p">(</span><span class="bp">cls</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span> <span class="n">returnType</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="n">StructType</span><span class="p">,</span> <span class="nb">str</span><span class="p">]])</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""Validate the handler class of a UDTF."""</span> |
| |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="nb">type</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">PySparkTypeError</span><span class="p">(</span> |
| <span class="n">error_class</span><span class="o">=</span><span class="s2">"INVALID_UDTF_HANDLER_TYPE"</span><span class="p">,</span> <span class="n">message_parameters</span><span class="o">=</span><span class="p">{</span><span class="s2">"type"</span><span class="p">:</span> <span class="nb">type</span><span class="p">(</span><span class="bp">cls</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span><span class="p">}</span> |
| <span class="p">)</span> |
| |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="s2">"eval"</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">PySparkAttributeError</span><span class="p">(</span> |
| <span class="n">error_class</span><span class="o">=</span><span class="s2">"INVALID_UDTF_NO_EVAL"</span><span class="p">,</span> <span class="n">message_parameters</span><span class="o">=</span><span class="p">{</span><span class="s2">"name"</span><span class="p">:</span> <span class="bp">cls</span><span class="o">.</span><span class="vm">__name__</span><span class="p">}</span> |
| <span class="p">)</span> |
| |
| <span class="n">has_analyze</span> <span class="o">=</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="s2">"analyze"</span><span class="p">)</span> |
| <span class="n">has_analyze_staticmethod</span> <span class="o">=</span> <span class="n">has_analyze</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span> |
| <span class="n">inspect</span><span class="o">.</span><span class="n">getattr_static</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="s2">"analyze"</span><span class="p">),</span> <span class="nb">staticmethod</span> |
| <span class="p">)</span> |
| <span class="k">if</span> <span class="n">returnType</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">has_analyze_staticmethod</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="n">PySparkAttributeError</span><span class="p">(</span> |
| <span class="n">error_class</span><span class="o">=</span><span class="s2">"INVALID_UDTF_RETURN_TYPE"</span><span class="p">,</span> <span class="n">message_parameters</span><span class="o">=</span><span class="p">{</span><span class="s2">"name"</span><span class="p">:</span> <span class="bp">cls</span><span class="o">.</span><span class="vm">__name__</span><span class="p">}</span> |
| <span class="p">)</span> |
| <span class="k">if</span> <span class="n">returnType</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">has_analyze</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="n">PySparkAttributeError</span><span class="p">(</span> |
| <span class="n">error_class</span><span class="o">=</span><span class="s2">"INVALID_UDTF_BOTH_RETURN_TYPE_AND_ANALYZE"</span><span class="p">,</span> |
| <span class="n">message_parameters</span><span class="o">=</span><span class="p">{</span><span class="s2">"name"</span><span class="p">:</span> <span class="bp">cls</span><span class="o">.</span><span class="vm">__name__</span><span class="p">},</span> |
| <span class="p">)</span> |
| |
| |
| <div class="viewcode-block" id="UserDefinedTableFunction"><a class="viewcode-back" href="../../../reference/pyspark.sql/api/pyspark.sql.udtf.UserDefinedTableFunction.html#pyspark.sql.UserDefinedTableFunction">[docs]</a><span class="k">class</span> <span class="nc">UserDefinedTableFunction</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""</span> |
| <span class="sd"> User-defined table function in Python</span> |
| |
| <span class="sd"> .. versionadded:: 3.5.0</span> |
| |
| <span class="sd"> Notes</span> |
| <span class="sd"> -----</span> |
| <span class="sd"> The constructor of this class is not supposed to be directly called.</span> |
| <span class="sd"> Use :meth:`pyspark.sql.functions.udtf` to create this instance.</span> |
| |
| <span class="sd"> This API is evolving.</span> |
| <span class="sd"> """</span> |
| |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span> |
| <span class="bp">self</span><span class="p">,</span> |
| <span class="n">func</span><span class="p">:</span> <span class="n">Type</span><span class="p">,</span> |
| <span class="n">returnType</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="n">StructType</span><span class="p">,</span> <span class="nb">str</span><span class="p">]],</span> |
| <span class="n">name</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> |
| <span class="n">evalType</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">PythonEvalType</span><span class="o">.</span><span class="n">SQL_TABLE_UDF</span><span class="p">,</span> |
| <span class="n">deterministic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> |
| <span class="p">):</span> |
| <span class="n">_validate_udtf_handler</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">returnType</span><span class="p">)</span> |
| |
| <span class="bp">self</span><span class="o">.</span><span class="n">func</span> <span class="o">=</span> <span class="n">func</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_returnType</span> <span class="o">=</span> <span class="n">returnType</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_returnType_placeholder</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">StructType</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_inputTypes_placeholder</span> <span class="o">=</span> <span class="kc">None</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_judtf_placeholder</span> <span class="o">=</span> <span class="kc">None</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_name</span> <span class="o">=</span> <span class="n">name</span> <span class="ow">or</span> <span class="n">func</span><span class="o">.</span><span class="vm">__name__</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">evalType</span> <span class="o">=</span> <span class="n">evalType</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">deterministic</span> <span class="o">=</span> <span class="n">deterministic</span> |
| |
| <span class="nd">@property</span> |
| <span class="k">def</span> <span class="nf">returnType</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">Optional</span><span class="p">[</span><span class="n">StructType</span><span class="p">]:</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_returnType</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">return</span> <span class="kc">None</span> |
| <span class="c1"># `_parse_datatype_string` accesses to JVM for parsing a DDL formatted string.</span> |
| <span class="c1"># This makes sure this is called after SparkContext is initialized.</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_returnType_placeholder</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_returnType</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span> |
| <span class="n">parsed</span> <span class="o">=</span> <span class="n">_parse_datatype_string</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_returnType</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">parsed</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_returnType</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">parsed</span><span class="p">,</span> <span class="n">StructType</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">PySparkTypeError</span><span class="p">(</span> |
| <span class="n">error_class</span><span class="o">=</span><span class="s2">"UDTF_RETURN_TYPE_MISMATCH"</span><span class="p">,</span> |
| <span class="n">message_parameters</span><span class="o">=</span><span class="p">{</span> |
| <span class="s2">"name"</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_name</span><span class="p">,</span> |
| <span class="s2">"return_type"</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">parsed</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="p">},</span> |
| <span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_returnType_placeholder</span> <span class="o">=</span> <span class="n">parsed</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_returnType_placeholder</span> |
| |
| <span class="nd">@property</span> |
| <span class="k">def</span> <span class="nf">_judtf</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="s2">"JavaObject"</span><span class="p">:</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_judtf_placeholder</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_judtf_placeholder</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_create_judtf</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">func</span><span class="p">)</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_judtf_placeholder</span> |
| |
| <span class="k">def</span> <span class="nf">_create_judtf</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">:</span> <span class="n">Type</span><span class="p">)</span> <span class="o">-></span> <span class="s2">"JavaObject"</span><span class="p">:</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql</span> <span class="kn">import</span> <span class="n">SparkSession</span> |
| |
| <span class="n">spark</span> <span class="o">=</span> <span class="n">SparkSession</span><span class="o">.</span><span class="n">_getActiveSessionOrCreate</span><span class="p">()</span> |
| <span class="n">sc</span> <span class="o">=</span> <span class="n">spark</span><span class="o">.</span><span class="n">sparkContext</span> |
| |
| <span class="k">try</span><span class="p">:</span> |
| <span class="n">wrapped_func</span> <span class="o">=</span> <span class="n">_wrap_function</span><span class="p">(</span><span class="n">sc</span><span class="p">,</span> <span class="n">func</span><span class="p">)</span> |
| <span class="k">except</span> <span class="n">pickle</span><span class="o">.</span><span class="n">PicklingError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span> |
| <span class="k">if</span> <span class="s2">"CONTEXT_ONLY_VALID_ON_DRIVER"</span> <span class="ow">in</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="n">PySparkPicklingError</span><span class="p">(</span> |
| <span class="n">error_class</span><span class="o">=</span><span class="s2">"UDTF_SERIALIZATION_ERROR"</span><span class="p">,</span> |
| <span class="n">message_parameters</span><span class="o">=</span><span class="p">{</span> |
| <span class="s2">"name"</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_name</span><span class="p">,</span> |
| <span class="s2">"message"</span><span class="p">:</span> <span class="s2">"it appears that you are attempting to reference SparkSession "</span> |
| <span class="s2">"inside a UDTF. SparkSession can only be used on the driver, "</span> |
| <span class="s2">"not in code that runs on workers. Please remove the reference "</span> |
| <span class="s2">"and try again."</span><span class="p">,</span> |
| <span class="p">},</span> |
| <span class="p">)</span> <span class="kn">from</span> <span class="kc">None</span> |
| <span class="k">raise</span> <span class="n">PySparkPicklingError</span><span class="p">(</span> |
| <span class="n">error_class</span><span class="o">=</span><span class="s2">"UDTF_SERIALIZATION_ERROR"</span><span class="p">,</span> |
| <span class="n">message_parameters</span><span class="o">=</span><span class="p">{</span> |
| <span class="s2">"name"</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_name</span><span class="p">,</span> |
| <span class="s2">"message"</span><span class="p">:</span> <span class="s2">"Please check the stack trace and make sure the "</span> |
| <span class="s2">"function is serializable."</span><span class="p">,</span> |
| <span class="p">},</span> |
| <span class="p">)</span> |
| |
| <span class="k">assert</span> <span class="n">sc</span><span class="o">.</span><span class="n">_jvm</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">returnType</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">judtf</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">sql</span><span class="o">.</span><span class="n">execution</span><span class="o">.</span><span class="n">python</span><span class="o">.</span><span class="n">UserDefinedPythonTableFunction</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_name</span><span class="p">,</span> <span class="n">wrapped_func</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">evalType</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">deterministic</span> |
| <span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">jdt</span> <span class="o">=</span> <span class="n">spark</span><span class="o">.</span><span class="n">_jsparkSession</span><span class="o">.</span><span class="n">parseDataType</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">returnType</span><span class="o">.</span><span class="n">json</span><span class="p">())</span> |
| <span class="n">judtf</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">sql</span><span class="o">.</span><span class="n">execution</span><span class="o">.</span><span class="n">python</span><span class="o">.</span><span class="n">UserDefinedPythonTableFunction</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_name</span><span class="p">,</span> <span class="n">wrapped_func</span><span class="p">,</span> <span class="n">jdt</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">evalType</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">deterministic</span> |
| <span class="p">)</span> |
| <span class="k">return</span> <span class="n">judtf</span> |
| |
| <span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">:</span> <span class="s2">"ColumnOrName"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="s2">"ColumnOrName"</span><span class="p">)</span> <span class="o">-></span> <span class="s2">"DataFrame"</span><span class="p">:</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql.classic.column</span> <span class="kn">import</span> <span class="n">_to_java_column</span><span class="p">,</span> <span class="n">_to_java_expr</span><span class="p">,</span> <span class="n">_to_seq</span> |
| |
| <span class="kn">from</span> <span class="nn">pyspark.sql</span> <span class="kn">import</span> <span class="n">DataFrame</span><span class="p">,</span> <span class="n">SparkSession</span> |
| |
| <span class="n">spark</span> <span class="o">=</span> <span class="n">SparkSession</span><span class="o">.</span><span class="n">_getActiveSessionOrCreate</span><span class="p">()</span> |
| <span class="n">sc</span> <span class="o">=</span> <span class="n">spark</span><span class="o">.</span><span class="n">sparkContext</span> |
| |
| <span class="k">assert</span> <span class="n">sc</span><span class="o">.</span><span class="n">_jvm</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> |
| <span class="n">jcols</span> <span class="o">=</span> <span class="p">[</span><span class="n">_to_java_column</span><span class="p">(</span><span class="n">arg</span><span class="p">)</span> <span class="k">for</span> <span class="n">arg</span> <span class="ow">in</span> <span class="n">args</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span> |
| <span class="n">sc</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">Column</span><span class="p">(</span> |
| <span class="n">sc</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">sql</span><span class="o">.</span><span class="n">catalyst</span><span class="o">.</span><span class="n">expressions</span><span class="o">.</span><span class="n">NamedArgumentExpression</span><span class="p">(</span> |
| <span class="n">key</span><span class="p">,</span> <span class="n">_to_java_expr</span><span class="p">(</span><span class="n">value</span><span class="p">)</span> |
| <span class="p">)</span> |
| <span class="p">)</span> |
| <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">items</span><span class="p">()</span> |
| <span class="p">]</span> |
| |
| <span class="n">judtf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_judtf</span> |
| <span class="n">jPythonUDTF</span> <span class="o">=</span> <span class="n">judtf</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">spark</span><span class="o">.</span><span class="n">_jsparkSession</span><span class="p">,</span> <span class="n">_to_seq</span><span class="p">(</span><span class="n">sc</span><span class="p">,</span> <span class="n">jcols</span><span class="p">))</span> |
| <span class="k">return</span> <span class="n">DataFrame</span><span class="p">(</span><span class="n">jPythonUDTF</span><span class="p">,</span> <span class="n">spark</span><span class="p">)</span> |
| |
| <div class="viewcode-block" id="UserDefinedTableFunction.asDeterministic"><a class="viewcode-back" href="../../../reference/pyspark.sql/api/pyspark.sql.udtf.UserDefinedTableFunction.asDeterministic.html#pyspark.sql.UserDefinedTableFunction.asDeterministic">[docs]</a> <span class="k">def</span> <span class="nf">asDeterministic</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="s2">"UserDefinedTableFunction"</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""</span> |
| <span class="sd"> Updates UserDefinedTableFunction to deterministic.</span> |
| <span class="sd"> """</span> |
| <span class="c1"># Explicitly clean the cache to create a JVM UDTF instance.</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_judtf_placeholder</span> <span class="o">=</span> <span class="kc">None</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">deterministic</span> <span class="o">=</span> <span class="kc">True</span> |
| <span class="k">return</span> <span class="bp">self</span></div></div> |
| |
| |
| <div class="viewcode-block" id="UDTFRegistration"><a class="viewcode-back" href="../../../reference/pyspark.sql/api/pyspark.sql.UDTFRegistration.html#pyspark.sql.UDTFRegistration">[docs]</a><span class="k">class</span> <span class="nc">UDTFRegistration</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""</span> |
| <span class="sd"> Wrapper for user-defined table function registration. This instance can be accessed by</span> |
| <span class="sd"> :attr:`spark.udtf` or :attr:`sqlContext.udtf`.</span> |
| |
| <span class="sd"> .. versionadded:: 3.5.0</span> |
| <span class="sd"> """</span> |
| |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sparkSession</span><span class="p">:</span> <span class="s2">"SparkSession"</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">sparkSession</span> <span class="o">=</span> <span class="n">sparkSession</span> |
| |
| <div class="viewcode-block" id="UDTFRegistration.register"><a class="viewcode-back" href="../../../reference/pyspark.sql/api/pyspark.sql.UDTFRegistration.register.html#pyspark.sql.UDTFRegistration.register">[docs]</a> <span class="k">def</span> <span class="nf">register</span><span class="p">(</span> |
| <span class="bp">self</span><span class="p">,</span> |
| <span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> |
| <span class="n">f</span><span class="p">:</span> <span class="s2">"UserDefinedTableFunction"</span><span class="p">,</span> |
| <span class="p">)</span> <span class="o">-></span> <span class="s2">"UserDefinedTableFunction"</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""Register a Python user-defined table function as a SQL table function.</span> |
| |
| <span class="sd"> .. versionadded:: 3.5.0</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> name : str</span> |
| <span class="sd"> The name of the user-defined table function in SQL statements.</span> |
| <span class="sd"> f : function or :meth:`pyspark.sql.functions.udtf`</span> |
| <span class="sd"> The user-defined table function.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> function</span> |
| <span class="sd"> The registered user-defined table function.</span> |
| |
| <span class="sd"> Notes</span> |
| <span class="sd"> -----</span> |
| <span class="sd"> Spark uses the return type of the given user-defined table function as the return</span> |
| <span class="sd"> type of the registered user-defined function.</span> |
| |
| <span class="sd"> To register a nondeterministic Python table function, users need to first build</span> |
| <span class="sd"> a nondeterministic user-defined table function and then register it as a SQL function.</span> |
| |
| <span class="sd"> Examples</span> |
| <span class="sd"> --------</span> |
| <span class="sd"> >>> from pyspark.sql.functions import udtf</span> |
| <span class="sd"> >>> @udtf(returnType="c1: int, c2: int")</span> |
| <span class="sd"> ... class PlusOne:</span> |
| <span class="sd"> ... def eval(self, x: int):</span> |
| <span class="sd"> ... yield x, x + 1</span> |
| <span class="sd"> ...</span> |
| <span class="sd"> >>> _ = spark.udtf.register(name="plus_one", f=PlusOne)</span> |
| <span class="sd"> >>> spark.sql("SELECT * FROM plus_one(1)").collect()</span> |
| <span class="sd"> [Row(c1=1, c2=2)]</span> |
| |
| <span class="sd"> Use it with lateral join</span> |
| |
| <span class="sd"> >>> spark.sql("SELECT * FROM VALUES (0, 1), (1, 2) t(x, y), LATERAL plus_one(x)").collect()</span> |
| <span class="sd"> [Row(x=0, y=1, c1=0, c2=1), Row(x=1, y=2, c1=1, c2=2)]</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="n">f</span><span class="o">.</span><span class="n">evalType</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">[</span><span class="n">PythonEvalType</span><span class="o">.</span><span class="n">SQL_TABLE_UDF</span><span class="p">,</span> <span class="n">PythonEvalType</span><span class="o">.</span><span class="n">SQL_ARROW_TABLE_UDF</span><span class="p">]:</span> |
| <span class="k">raise</span> <span class="n">PySparkTypeError</span><span class="p">(</span> |
| <span class="n">error_class</span><span class="o">=</span><span class="s2">"INVALID_UDTF_EVAL_TYPE"</span><span class="p">,</span> |
| <span class="n">message_parameters</span><span class="o">=</span><span class="p">{</span> |
| <span class="s2">"name"</span><span class="p">:</span> <span class="n">name</span><span class="p">,</span> |
| <span class="s2">"eval_type"</span><span class="p">:</span> <span class="s2">"SQL_TABLE_UDF, SQL_ARROW_TABLE_UDF"</span><span class="p">,</span> |
| <span class="p">},</span> |
| <span class="p">)</span> |
| |
| <span class="n">register_udtf</span> <span class="o">=</span> <span class="n">_create_udtf</span><span class="p">(</span> |
| <span class="bp">cls</span><span class="o">=</span><span class="n">f</span><span class="o">.</span><span class="n">func</span><span class="p">,</span> |
| <span class="n">returnType</span><span class="o">=</span><span class="n">f</span><span class="o">.</span><span class="n">returnType</span><span class="p">,</span> |
| <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> |
| <span class="n">evalType</span><span class="o">=</span><span class="n">f</span><span class="o">.</span><span class="n">evalType</span><span class="p">,</span> |
| <span class="n">deterministic</span><span class="o">=</span><span class="n">f</span><span class="o">.</span><span class="n">deterministic</span><span class="p">,</span> |
| <span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">sparkSession</span><span class="o">.</span><span class="n">_jsparkSession</span><span class="o">.</span><span class="n">udtf</span><span class="p">()</span><span class="o">.</span><span class="n">registerPython</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">register_udtf</span><span class="o">.</span><span class="n">_judtf</span><span class="p">)</span> |
| <span class="k">return</span> <span class="n">register_udtf</span></div></div> |
| |
| |
| <span class="k">def</span> <span class="nf">_test</span><span class="p">()</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span> |
| <span class="kn">import</span> <span class="nn">doctest</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql</span> <span class="kn">import</span> <span class="n">SparkSession</span> |
| <span class="kn">import</span> <span class="nn">pyspark.sql.udf</span> |
| |
| <span class="n">globs</span> <span class="o">=</span> <span class="n">pyspark</span><span class="o">.</span><span class="n">sql</span><span class="o">.</span><span class="n">udtf</span><span class="o">.</span><span class="vm">__dict__</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> |
| <span class="n">spark</span> <span class="o">=</span> <span class="n">SparkSession</span><span class="o">.</span><span class="n">builder</span><span class="o">.</span><span class="n">master</span><span class="p">(</span><span class="s2">"local[4]"</span><span class="p">)</span><span class="o">.</span><span class="n">appName</span><span class="p">(</span><span class="s2">"sql.udtf tests"</span><span class="p">)</span><span class="o">.</span><span class="n">getOrCreate</span><span class="p">()</span> |
| <span class="n">globs</span><span class="p">[</span><span class="s2">"spark"</span><span class="p">]</span> <span class="o">=</span> <span class="n">spark</span> |
| <span class="p">(</span><span class="n">failure_count</span><span class="p">,</span> <span class="n">test_count</span><span class="p">)</span> <span class="o">=</span> <span class="n">doctest</span><span class="o">.</span><span class="n">testmod</span><span class="p">(</span> |
| <span class="n">pyspark</span><span class="o">.</span><span class="n">sql</span><span class="o">.</span><span class="n">udtf</span><span class="p">,</span> <span class="n">globs</span><span class="o">=</span><span class="n">globs</span><span class="p">,</span> <span class="n">optionflags</span><span class="o">=</span><span class="n">doctest</span><span class="o">.</span><span class="n">ELLIPSIS</span> <span class="o">|</span> <span class="n">doctest</span><span class="o">.</span><span class="n">NORMALIZE_WHITESPACE</span> |
| <span class="p">)</span> |
| <span class="n">spark</span><span class="o">.</span><span class="n">stop</span><span class="p">()</span> |
| <span class="k">if</span> <span class="n">failure_count</span><span class="p">:</span> |
| <span class="n">sys</span><span class="o">.</span><span class="n">exit</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span> |
| |
| |
| <span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s2">"__main__"</span><span class="p">:</span> |
| <span class="n">_test</span><span class="p">()</span> |
| </pre></div> |
| |
| </article> |
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