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| <h1 class="title">Function Invocation</h1> |
| |
| |
| <h3 id="description">Description</h3> |
| |
| <p>A function invocation executes a builtin function or a user-defined function after associating arguments to the function’s parameters.</p> |
| |
| <p>Spark supports positional parameter invocation as well as named parameter invocation.</p> |
| |
| <h4 id="positional-parameter-invocation">Positional parameter invocation</h4> |
| |
| <p>Each argument is assigned to the matching parameter at the position it is specified.</p> |
| |
| <p>This notation can be used by all functions unless it is explicitly documented that named parameter invocation is required.</p> |
| |
| <p>If the function supports optional parameters, trailing parameters for which no arguments have been specified, are defaulted.</p> |
| |
| <h4 id="named-parameter-invocation">Named parameter invocation</h4> |
| |
| <p>Arguments are explicitly assigned to parameters using the parameter names published by the function.</p> |
| |
| <p>This notation must be used for a select subset of built-in functions which allow numerous optional parameters, making positional parameter invocation impractical. |
| These functions may allow a mixed invocation where a leading set of parameters are expected to be assigned by position and the trailing, optional set of parameters by name.</p> |
| |
| <h3 id="syntax">Syntax</h3> |
| |
| <div class="language-sql highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">function_name</span> <span class="p">(</span> <span class="p">[</span> <span class="n">argExpr</span> <span class="o">|</span> <span class="n">table_argument</span> <span class="p">]</span> <span class="p">[,</span> <span class="p">...]</span> |
| <span class="p">[</span> <span class="n">namedParameter</span> <span class="o">=></span> <span class="p">[</span> <span class="n">argExpr</span> <span class="o">|</span> <span class="n">table_argument</span> <span class="p">]</span> <span class="p">[,</span> <span class="p">...]</span> <span class="p">)</span> |
| |
| <span class="n">table_argument</span> |
| <span class="p">{</span> <span class="k">TABLE</span> <span class="p">(</span> <span class="p">{</span> <span class="k">table_name</span> <span class="o">|</span> <span class="n">query</span> <span class="p">}</span> <span class="p">)</span> |
| <span class="p">[</span> <span class="n">table_partition</span> <span class="p">]</span> |
| <span class="p">[</span> <span class="n">table_order</span> <span class="p">]</span> |
| |
| <span class="n">table_partitioning</span> |
| <span class="p">{</span> <span class="k">WITH</span> <span class="n">SINGLE</span> <span class="k">PARTITION</span> <span class="o">|</span> |
| <span class="p">{</span> <span class="k">PARTITION</span> <span class="o">|</span> <span class="n">DISTRIBUTE</span> <span class="p">}</span> <span class="k">BY</span> <span class="p">{</span> <span class="n">partition_expr</span> <span class="o">|</span> <span class="p">(</span> <span class="n">partition_expr</span> <span class="p">[,</span> <span class="p">...]</span> <span class="p">)</span> <span class="p">}</span> <span class="p">}</span> |
| |
| <span class="n">table_ordering</span> |
| <span class="p">{</span> <span class="p">{</span> <span class="k">ORDER</span> <span class="o">|</span> <span class="n">SORT</span> <span class="p">}</span> <span class="k">BY</span> <span class="p">{</span> <span class="n">order_by_expr</span> <span class="o">|</span> <span class="p">(</span> <span class="n">order_by_expr</span> <span class="p">[,</span> <span class="p">...]</span> <span class="p">}</span> <span class="p">}</span> |
| </code></pre></div></div> |
| |
| <h3 id="parameters">Parameters</h3> |
| |
| <ul> |
| <li> |
| <p><strong>function_name</strong></p> |
| |
| <p>The name of the built-in or user defined function. When resolving an unqualified function_name Spark will first consider a built-in or temporary function, and then a function in the current schema.</p> |
| </li> |
| <li> |
| <p><strong>argExpr</strong></p> |
| |
| <p>Any expression which can be implicitly cast to the parameter it is associated with.</p> |
| |
| <p>The function may impose further restriction on the argument such as mandating literals, constant expressions, or specific values.</p> |
| </li> |
| <li> |
| <p><strong>namedParameter</strong></p> |
| |
| <p>The unqualified name of a parameter to which the argExpr will be assigned.</p> |
| |
| <p>Named parameter notation is supported for Python UDF, and specific built-in functions.</p> |
| </li> |
| <li> |
| <p><strong>table_argument</strong></p> |
| |
| <p>Specifies an argument for a parameter that is a table.</p> |
| |
| <ul> |
| <li> |
| <p><strong>TABLE ( table_name )</strong></p> |
| |
| <p>Identifies a table to pass to the function by name.</p> |
| </li> |
| <li> |
| <p><strong>TABLE ( query )</strong></p> |
| |
| <p>Passes the result of query to the function.</p> |
| </li> |
| <li> |
| <p><strong>table-partitioning</strong></p> |
| |
| <p>Optionally specifies that the table argument is partitioned. If not specified the partitioning is determined by Spark.</p> |
| |
| <ul> |
| <li> |
| <p><strong>WITH SINGLE PARTITION</strong></p> |
| |
| <p>The table argument is not partitioned.</p> |
| </li> |
| <li> |
| <p><strong>partition_expr</strong></p> |
| |
| <p>One or more expressions defining how to partition the table argument. Each expression can be composed of columns presents in the table argument, literals, parameters, variables, and deterministic functions.</p> |
| </li> |
| <li> |
| <p><strong>table_ordering</strong></p> |
| |
| <p>Optionally specifies an order in which the result rows of each partition of the table argument are passed to the function.</p> |
| |
| <p>By default, the order is undefined.</p> |
| |
| <ul> |
| <li> |
| <p><strong>order_by_expr</strong></p> |
| |
| <p>One or more expressions. Each expression can be composed of columns presents in the table argument, literals, parameters, variables, and deterministic functions.</p> |
| </li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
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