{"id":16494,"date":"2018-05-27T06:10:55","date_gmt":"2018-05-27T06:10:55","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=16494"},"modified":"2021-05-09T13:10:45","modified_gmt":"2021-05-09T07:40:45","slug":"impala-udf","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/impala-udf\/","title":{"rendered":"Impala UDF (User-Defined Functions) &#8211; How to Write UDFs"},"content":{"rendered":"<p><span style=\"font-weight: 400\">In this <strong>Impala Tutorial<\/strong>, we will learn the whole concept of Apache Impala\u00a0UDF\u00a0(User-Defined Functions). Apart from Impala UDF introduction, we will also learn, how to write Impala User-Defined Functions (UDFs) in detail. <\/span><\/p>\n<p><span style=\"font-weight: 400\">In addition, we will see limitations of Impala UDFs to prevent any error while using it. At last, we will cover some Impala UDF samples.<\/span><\/p>\n<p>So, let&#8217;s start Impala UDF (User-Defined Functions)<\/p>\n<h2><span style=\"font-weight: 400\">Impala User-Defined Functions (UDFs)<\/span><\/h2>\n<p><span style=\"font-weight: 400\">In order to code our own application logic for processing column values during an Impala query, we use User-Defined Functions. Impala User-defined functions are frequently abbreviated as UDFs. <\/span><\/p>\n<p><span style=\"font-weight: 400\">For example, using an external math library- a UDF could perform calculations, also it can combine several column values into one, it can perform geospatial calculations, or other kinds of tests and transformations especially those are outside the scope of the built-in SQL operators and functions.<\/span><\/p>\n<p><span style=\"font-weight: 400\">In other words, to simplify query logic when producing reports, or in order to transform data in flexible ways while using INSERT &#8230; SELECT syntax to copy from one table to another, we can use UDFs.<\/span><\/p>\n<p><span style=\"font-weight: 400\">Also, under names stored functions or stored routines this feature is available in other database products.<\/span><\/p>\n<p><span style=\"font-weight: 400\">In Impala 1.2 and higher, Impala support for UDF is available:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Using UDFs in a query required using the <strong>Hive <\/strong>shell, in Impala 1.1.<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">After Impala 1.2, we can run both \u00a0<strong>Java<\/strong>-based <strong>Hive UDFs <\/strong>that you might already have written and high-performance native code UDFs written in C++.<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Impala UDAFs can run and return a value based on a set of rows and scalar UDFs that return a single value for each row of the result set.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\"><strong>Note:<\/strong> There is no support for User-Defined Table Functions (UDTFs) or window functions, in Impala currently.<\/span><\/p>\n<h2><span style=\"font-weight: 400\">Impala UDF Concepts<\/span><\/h2>\n<p><span style=\"font-weight: 400\">Basically, we can write all-new functions on the basis of our use case. Moreover, it is possible to reuse Java UDFs which we have already written for Hive. However, for producing results one row at a time, we can code either scalar functions or more complex aggregate functions.<\/span><\/p>\n<div id=\"attachment_16660\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Impala-UDF-Concepts-01.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-16660\" class=\"wp-image-16660 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Impala-UDF-Concepts-01.jpg\" alt=\"Impala UDF Concepts\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Impala-UDF-Concepts-01.jpg 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Impala-UDF-Concepts-01-150x79.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Impala-UDF-Concepts-01-300x157.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Impala-UDF-Concepts-01-768x402.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Impala-UDF-Concepts-01-1024x536.jpg 1024w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-16660\" class=\"wp-caption-text\">Impala UDF Concepts<\/p><\/div>\n<h3>a. Impala UDFs and UDAFs<\/h3>\n<p><span style=\"font-weight: 400\">In Impala UDF, we write might accept or produce different numbers of input and output values, on the basis of our use case:<\/span><\/p>\n<p><span style=\"font-weight: 400\">One of the most general forms of UDF takes a single input value and returns a single output value. However, it is called once for each row in the result set, while used in a query.<\/span><br \/>\n<strong> For example:<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\">select Employee_name, is_frequent_Employee(Employee_id) from Employees;\nselect obfuscate(sensitive_column) from sensitive_data;<\/pre>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Although, a (UDAF) returns a single value after accepting a group of values.\u00a0<\/span><\/li>\n<\/ul>\n<p><strong>For example:<\/strong><br \/>\n&#8212; It evaluates multiple rows, however, returns a single value.<\/p>\n<pre class=\"EnlighterJSRAW\">select most_profitable_location(store_id, sales, expenses, tax_rate, depreciation) from franchise_data group by year;<\/pre>\n<pre class=\"EnlighterJSRAW\">select closest_Hotel(latitude, longitude) from places;<\/pre>\n<p>&#8212; Evaluates batches of rows and returns a separate value for each batch.<\/p>\n<h3><span style=\"font-weight: 400\">b. Native Impala UDF<\/span><\/h3>\n<p><span style=\"font-weight: 400\">In addition to supporting existing Hive UDFs written in Java, Impala supports UDFs written in C++ as well. However, we use C++ UDFs while practical. <\/span><\/p>\n<p><span style=\"font-weight: 400\">The reason behind it is the compiled native code can yield higher performance because of UDF execution time often 10x faster for a C++ on comparing to Java UDF.<\/span><\/p>\n<h3>c. Using Hive UDF with Impala<\/h3>\n<p><span style=\"font-weight: 400\">There is a flexibility that User-Defined Functions (UDFs), which originally written for Hive, Impala can run them, even with no changes, but only subject to the several conditions:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">It is must that the parameters and return value all should use scalar data types which are supported by Impala. For example, complex or nested types.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Moreover, Impala does not support Hive UDFs that accept or return the TIMESTAMP.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Here, both Hive UDAFs and UDTFs are not supported.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\"> UDF execution time often 10x faster for a C++ on comparing to Java UDF.<\/span><\/li>\n<\/ul>\n<h2><span style=\"font-weight: 400\">Install &#8211; Impala UDF &amp; Development Package<\/span><\/h2>\n<p><span style=\"font-weight: 400\">Initially, download and install the impala-udf-devel package or impala-udf-dev, in order to develop Impala UDF. There are header files, sample source, and build configuration files, in this package.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">For our operating system version, locate the appropriate .repo or list file.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Specify impala-udf-devel or impala-udf-dev, for the package name.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">In addition, there is an advantage that it is not necessary that UDF development code relies on Impala being installed on the same machine. Because it is possible to write and compile UDFs on a minimal development system, and further deploy them on a different one for use with Impala.<\/span><\/p>\n<h2><span style=\"font-weight: 400\">How to Write Impala UDF?<\/span><\/h2>\n<p><span style=\"font-weight: 400\">Follow these steps while writing Impala UDFs:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Once we transfer values from the high-level SQL to your lower-level Impala UDF code, remember the data type differences.<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">For function-oriented programming, use best practices, like : <\/span><\/li>\n<\/ul>\n<ol>\n<li><span style=\"font-weight: 400\"> Select arguments carefully.<\/span><\/li>\n<li><span style=\"font-weight: 400\"> Try to avoid side effects.<\/span><\/li>\n<li>Also, make each function do a single thing.<\/li>\n<\/ol>\n<div id=\"attachment_16655\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Writing-Impala-UDF-01.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-16655\" class=\"wp-image-16655 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Writing-Impala-UDF-01.jpg\" alt=\"Impala UDF\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Writing-Impala-UDF-01.jpg 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Writing-Impala-UDF-01-150x79.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Writing-Impala-UDF-01-300x157.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Writing-Impala-UDF-01-768x402.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Writing-Impala-UDF-01-1024x536.jpg 1024w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-16655\" class=\"wp-caption-text\">How to Write Impala<\/p><\/div>\n<h3><span style=\"font-weight: 400\">a. Getting Started with UDF Coding<\/span><\/h3>\n<p><span style=\"font-weight: 400\">At very first, examine the header file \/usr\/include\/impala_udf\/udf.h, in order to understand the layout and member variables and functions of the predefined UDF data types:<\/span><br \/>\n<b><\/b><\/p>\n<p><b>\/\/ This is the only Impala header required to develop UDFs and UDAs.<\/b> This header<br \/>\n<b>\/\/ contains the types that need to be used and the FunctionContext object.<\/b> The context<br \/>\n<b>\/\/ object serves as the interface object between the UDF\/UDA and the impala process<\/b><\/p>\n<p><span style=\"font-weight: 400\">However, see the header file udf-sample.h within the sample build environment, that describes a simple function named AddUdf(), for the basic declarations needed to write a scalar UDF:<\/span><\/p>\n<pre class=\"EnlighterJSRAW\">#ifndef IMPALA_UDF_SAMPLE_UDF_H\n#define IMPALA_UDF_SAMPLE_UDF_H\n#include &lt;impala_udf\/udf.h&gt;\nusing namespace impala_udf;\nIntVal AddUdf(FunctionContext* context, const IntVal&amp; arg1, const IntVal&amp; arg2);\n#endif<\/pre>\n<p><span style=\"font-weight: 400\">Also, see the source file udf-sample.cc within the sample build environment, for sample C++ code for a simple function named AddUdf():<\/span><\/p>\n<pre class=\"EnlighterJSRAW\">#include \"udf-sample.h\"\n\/\/ In this sample, we are declaring a UDF that adds two ints and returns an int.\nIntVal AddUdf(FunctionContext* context, const IntVal&amp; arg1, const IntVal&amp; arg2) {\n\u00a0if (arg1.is_null || arg2.is_null) return IntVal::null();\n\u00a0return IntVal(arg1.val + arg2.val);\n}\n\/\/ Multiple UDFs can be defined in the same file<\/pre>\n<h3><span style=\"font-weight: 400\">b. Variable-Length Argument Lists<\/span><\/h3>\n<p><span style=\"font-weight: 400\">However, there are a fixed number of arguments in Impala UDF, in the signature of our C++ function, with each one named explicitly. Furthermore, our function can also accept additional optional arguments, where all of the same type. <\/span><\/p>\n<p><strong>For example<\/strong>,\u00a0let&#8217;s concatenate two strings, three strings, four strings, and so on or instead of that we can also compare two numbers, three numbers, four numbers, and so on.<br \/>\n<span style=\"font-weight: 400\">To accept a variable-length argument list, code the signature of your function like this:<\/span><\/p>\n<pre class=\"EnlighterJSRAW\">StringVal Concat(FunctionContext* context, const StringVal&amp; separator,\n\u00a0int num_var_args, const StringVal* args);<\/pre>\n<p><span style=\"font-weight: 400\">After the type of the first optional argument, in the CREATE FUNCTION statement, include &#8230; to indicate it could be followed by more arguments of the same type. <\/span><\/p>\n<p><span style=\"font-weight: 400\"><strong>For example<\/strong>, followed by one or more additional STRING arguments, the following function accepts a STRING argument:<\/span><\/p>\n<pre class=\"EnlighterJSRAW\">[localhost:21000] &gt; create function my_concat(string, string ...) returns string location '\/user\/test_user\/udfs\/sample.so' symbol='Concat';<\/pre>\n<p><span style=\"font-weight: 400\">The call from the SQL query must pass at least one argument to the variable-length portion of the argument list.<\/span><\/p>\n<p><span style=\"font-weight: 400\">When Impala calls the function, it fills in the initial set of required arguments, then passes the number of extra arguments and a pointer to the first of those optional arguments.<\/span><\/p>\n<h3>c. Handling NULL Values<\/h3>\n<p><span style=\"font-weight: 400\">It is essential for each Impala UDF to handle all situations where any NULL values are passed to our function, especially for correctness, performance, and reliability.<\/span><span style=\"font-family: Georgia, Georgia, serif;font-weight: inherit\">\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400\">In addition, we can construct a null instance of the return type by using its null() member function, if our function returns NULL when passed a NULL value. Even in other cases like when a search string does not found, we can do it.<\/span><\/p>\n<h3>d. Memory Allocation for Impala UDF<\/h3>\n<p><span style=\"font-weight: 400\">Before the query is finished, memory allocated within a Impala UDF is deallocated when the function exits, by default. Also, we can refer to input arguments in the expressions for our return values, because the input arguments remain allocated for the lifetime of the function.<\/span><span style=\"font-family: Georgia, Georgia, serif;font-weight: inherit\">\u00a0<\/span><\/p>\n<h3>e. Thread-Safe Work Area for Impala UDF<\/h3>\n<p><span style=\"font-weight: 400\">If we specify the optional PREPARE_FN and CLOSE_FN clauses on the CREATE FUNCTION statement, the performance of UDFs can improve. <\/span><\/p>\n<p><span style=\"font-weight: 400\">Here, the &#8220;prepare&#8221; function refers to the function which sets up a thread-safe data structure in memory\u00a0which we also can use as a work area whereas the &#8220;close&#8221; function refers to the function which deallocates that memory.<\/span><\/p>\n<h3>f. Error Handling for Impala UDFs<\/h3>\n<p><span style=\"font-weight: 400\">Error Handling for UDFs means, in order to prevent errors for UDFs we can call functions\u00a0which are members of the initial FunctionContext* argument passed to our function.<\/span><\/p>\n<p><span style=\"font-weight: 400\">Moreover, there are some conditions\u00a0which indicate minor, recoverable problems\u00a0which do not cause the query to stop, a UDF can record one or more warnings for that.<\/span><\/p>\n<pre class=\"EnlighterJSRAW\">bool AddWarning(const char* warning_msg);<\/pre>\n<p><span style=\"font-weight: 400\">Also, Impala UDF can set an error flag that prevents the query from returning any results, for a serious problem that requires canceling the query.<\/span><\/p>\n<pre class=\"EnlighterJSRAW\">void SetError(const char* error_msg);\u00a0\nbool AddWarning(const char* warning_msg);<\/pre>\n<p><span style=\"font-weight: 400\">Also, Impala UDF can set an error flag that prevents the query from returning any results, for a serious problem that requires canceling the query.<\/span><\/p>\n<pre class=\"EnlighterJSRAW\">void SetError(const char* error_msg);\n<\/pre>\n<h2><span style=\"font-weight: 400\">Performance Considerations for Impala UDFs<\/span><\/h2>\n<p><span style=\"font-weight: 400\">The performance of each Impala UDF is a critical factor in the speed of the overall ETL or ELT pipeline, since Impala UDF typically processes each row of a table, potentially being called billions of times. <\/span><\/p>\n<p><span style=\"font-weight: 400\">When the function is called over and over when processing a huge result set even small optimizations, we can make within the function body can return us big results.<\/span><\/p>\n<h2><span style=\"font-weight: 400\">Impala UDF Security Considerations\u00a0<\/span><\/h2>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">It is must to have the required read privilege for any databases and tables used in the query, in order to call an Impala UDF in a query.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Impala UDFs which are incorrectly coded may cause performance or capacity issues.<\/span><\/li>\n<\/ul>\n<h2><span style=\"font-weight: 400\">Limitations &amp; Restrictions for Impala User-Defined Functions<\/span><\/h2>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Hive UDFs which accept or return composite or nested types, or even other types which are not available in Impala tables, Impala does not support them.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Through Impala, we cannot call Hive current_user() function from a Java UDF.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Even, it does not support user-defined table functions (UDTFs) currently.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Moreover, it is not possible to use the CHAR and VARCHAR types as input arguments or return values for UDFs.<\/span><\/li>\n<\/ul>\n<p>So, this was all about Impala UDF. Hope you like our explanation.<\/p>\n<h2><span style=\"font-weight: 400\">Conclusion &#8211; Impala UDF<\/span><\/h2>\n<p><span style=\"font-weight: 400\">As a result, we have seen the whole concept of Impala user-defined functions (UDFs). In addition, we discuss how to write Impala UDF and install Impala UDFs. <\/span><\/p>\n<p><span style=\"font-weight: 400\">In conclusion, we saw performance &amp; security considerations for impala UDF with some limitations of Impala user-defined functions. Furthermore, if you have a doubt in Impala UDF, feel free to ask in comment box.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this Impala Tutorial, we will learn the whole concept of Apache Impala\u00a0UDF\u00a0(User-Defined Functions). Apart from Impala UDF introduction, we will also learn, how to write Impala User-Defined Functions (UDFs) in detail. In addition,&#46;&#46;&#46;<\/p>\n","protected":false},"author":6,"featured_media":16662,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[27],"tags":[6402,6570,6572,6577,6582,9007,15130,15285,15765],"class_list":["post-16494","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-impala","tag-how-to-write-impala-udf","tag-impala-udf","tag-impala-udfs","tag-impala-user-defined-functions","tag-impala-udf-devel","tag-native-impala-udfs","tag-udfs-and-udafs","tag-using-hive-udfs-with-impala","tag-what-is-impala-udfs"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Impala UDF (User-Defined Functions) - How to Write UDFs - DataFlair<\/title>\n<meta name=\"description\" content=\"Impala UDF Tutorial- Impala user-defined functions,Imapla-udf-devel,how to write UDF in Impala,performance.security consideration,limitations of Impala UDFs\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/impala-udf\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Impala UDF (User-Defined Functions) - How to Write UDFs - DataFlair\" \/>\n<meta property=\"og:description\" content=\"Impala UDF Tutorial- Impala user-defined functions,Imapla-udf-devel,how to write UDF in Impala,performance.security consideration,limitations of Impala UDFs\" \/>\n<meta property=\"og:url\" content=\"https:\/\/data-flair.training\/blogs\/impala-udf\/\" \/>\n<meta property=\"og:site_name\" content=\"DataFlair\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/DataFlairWS\/\" \/>\n<meta property=\"article:published_time\" content=\"2018-05-27T06:10:55+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2021-05-09T07:40:45+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Impala-User-Defined-Functions-UDFs-01-1.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"628\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"DataFlair Team\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:site\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"DataFlair Team\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"9 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Impala UDF (User-Defined Functions) - How to Write UDFs - DataFlair","description":"Impala UDF Tutorial- Impala user-defined functions,Imapla-udf-devel,how to write UDF in Impala,performance.security consideration,limitations of Impala UDFs","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/data-flair.training\/blogs\/impala-udf\/","og_locale":"en_US","og_type":"article","og_title":"Impala UDF (User-Defined Functions) - How to Write UDFs - DataFlair","og_description":"Impala UDF Tutorial- Impala user-defined functions,Imapla-udf-devel,how to write UDF in Impala,performance.security consideration,limitations of Impala UDFs","og_url":"https:\/\/data-flair.training\/blogs\/impala-udf\/","og_site_name":"DataFlair","article_publisher":"https:\/\/www.facebook.com\/DataFlairWS\/","article_published_time":"2018-05-27T06:10:55+00:00","article_modified_time":"2021-05-09T07:40:45+00:00","og_image":[{"width":1200,"height":628,"url":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/05\/Impala-User-Defined-Functions-UDFs-01-1.jpg","type":"image\/jpeg"}],"author":"DataFlair Team","twitter_card":"summary_large_image","twitter_creator":"@DataFlairWS","twitter_site":"@DataFlairWS","twitter_misc":{"Written by":"DataFlair Team","Est. reading time":"9 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/data-flair.training\/blogs\/impala-udf\/#article","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/impala-udf\/"},"author":{"name":"DataFlair Team","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/2c58ecb4f73a39f0ef993f1ddfcd7b89"},"headline":"Impala UDF (User-Defined Functions) &#8211; 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