to 0 and 1 minute is added to the final timestamp. The final state is converted trim(LEADING trimStr FROM str) - Remove the leading trimStr characters from str. It defines an aggregation from one or more pandas.Series to a scalar value, where each pandas.Series represents a column within the group or window. transform_keys(expr, func) - Transforms elements in a map using the function. element_at(array, index) - Returns element of array at given (1-based) index. It starts If the sec argument equals to 60, the seconds field is set If you look at https://medium.com/@manuzhang/the-hidden-cost-of-spark-withcolumn-8ffea517c015 then you see that withColumn with a foldLeft has known performance issues. The pattern is a string which is matched literally and Connect and share knowledge within a single location that is structured and easy to search. ltrim(str) - Removes the leading space characters from str. date_diff(endDate, startDate) - Returns the number of days from startDate to endDate. Returns NULL if the string 'expr' does not match the expected format. wrapped by angle brackets if the input value is negative. unix_seconds(timestamp) - Returns the number of seconds since 1970-01-01 00:00:00 UTC. 'S' or 'MI': Specifies the position of a '-' or '+' sign (optional, only allowed once at This character may only be specified limit - an integer expression which controls the number of times the regex is applied. to_json(expr[, options]) - Returns a JSON string with a given struct value. soundex(str) - Returns Soundex code of the string. raise_error(expr) - Throws an exception with expr. NULL elements are skipped. to_timestamp_ntz(timestamp_str[, fmt]) - Parses the timestamp_str expression with the fmt expression java.lang.Math.tanh. ceiling(expr[, scale]) - Returns the smallest number after rounding up that is not smaller than expr. shiftrightunsigned(base, expr) - Bitwise unsigned right shift. named_struct(name1, val1, name2, val2, ) - Creates a struct with the given field names and values. bin(expr) - Returns the string representation of the long value expr represented in binary. timezone - the time zone identifier. The result is one plus the Spark SQL alternatives to groupby/pivot/agg/collect_list using foldLeft java_method(class, method[, arg1[, arg2 ..]]) - Calls a method with reflection. Making statements based on opinion; back them up with references or personal experience. try_to_binary(str[, fmt]) - This is a special version of to_binary that performs the same operation, but returns a NULL value instead of raising an error if the conversion cannot be performed. targetTz - the time zone to which the input timestamp should be converted. octet_length(expr) - Returns the byte length of string data or number of bytes of binary data. max_by(x, y) - Returns the value of x associated with the maximum value of y. md5(expr) - Returns an MD5 128-bit checksum as a hex string of expr. ',' or 'G': Specifies the position of the grouping (thousands) separator (,). array_sort(expr, func) - Sorts the input array. array_join(array, delimiter[, nullReplacement]) - Concatenates the elements of the given array end of the string. expr1, expr3 - the branch condition expressions should all be boolean type. array_except(array1, array2) - Returns an array of the elements in array1 but not in array2, collect_list(expr) - Collects and returns a list of non-unique elements. reflect(class, method[, arg1[, arg2 ..]]) - Calls a method with reflection. typeof(expr) - Return DDL-formatted type string for the data type of the input. Notes The function is non-deterministic because the order of collected results depends on the order of the rows which may be non-deterministic after a shuffle. rand([seed]) - Returns a random value with independent and identically distributed (i.i.d.) If isIgnoreNull is true, returns only non-null values. some(expr) - Returns true if at least one value of expr is true. --conf "spark.executor.extraJavaOptions=-XX:-DontCompileHugeMethods" After that I am using cols.foldLeft(aggDF)((df, x) => df.withColumn(x, when(size(col(x)) > 0, col(x)).otherwise(lit(null)))) to replace empty array with null. any_value(expr[, isIgnoreNull]) - Returns some value of expr for a group of rows. Unless specified otherwise, uses the column name pos for position, col for elements of the array or key and value for elements of the map. The result data type is consistent with the value of configuration spark.sql.timestampType. Examples >>> Supported combinations of (mode, padding) are ('ECB', 'PKCS') and ('GCM', 'NONE'). explode(expr) - Separates the elements of array expr into multiple rows, or the elements of map expr into multiple rows and columns. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. value of default is null. it throws ArrayIndexOutOfBoundsException for invalid indices. Supported types are: byte, short, integer, long, date, timestamp. for invalid indices. a character string, and with zeros if it is a byte sequence. from_unixtime(unix_time[, fmt]) - Returns unix_time in the specified fmt. For example, add the option Content Discovery initiative April 13 update: Related questions using a Review our technical responses for the 2023 Developer Survey, Extract column values of Dataframe as List in Apache Spark, Scala map list based on list element index, Method for reducing memory load of Spark program. Valid modes: ECB, GCM. array_distinct(array) - Removes duplicate values from the array. date_str - A string to be parsed to date. split(str, regex, limit) - Splits str around occurrences that match regex and returns an array with a length of at most limit. If partNum is 0, end of the string, TRAILING, FROM - these are keywords to specify trimming string characters from the right 0 to 60. default - a string expression which is to use when the offset row does not exist. substr(str, pos[, len]) - Returns the substring of str that starts at pos and is of length len, or the slice of byte array that starts at pos and is of length len. percentage array. The start of the range. If the regular expression is not found, the result is null. locate(substr, str[, pos]) - Returns the position of the first occurrence of substr in str after position pos. first(expr[, isIgnoreNull]) - Returns the first value of expr for a group of rows. posexplode_outer(expr) - Separates the elements of array expr into multiple rows with positions, or the elements of map expr into multiple rows and columns with positions. cbrt(expr) - Returns the cube root of expr. Key lengths of 16, 24 and 32 bits are supported. The positions are numbered from right to left, starting at zero. For example, 2005-01-02 is part of the 53rd week of year 2004, while 2012-12-31 is part of the first week of 2013, "DAY", ("D", "DAYS") - the day of the month field (1 - 31), "DAYOFWEEK",("DOW") - the day of the week for datetime as Sunday(1) to Saturday(7), "DAYOFWEEK_ISO",("DOW_ISO") - ISO 8601 based day of the week for datetime as Monday(1) to Sunday(7), "DOY" - the day of the year (1 - 365/366), "HOUR", ("H", "HOURS", "HR", "HRS") - The hour field (0 - 23), "MINUTE", ("M", "MIN", "MINS", "MINUTES") - the minutes field (0 - 59), "SECOND", ("S", "SEC", "SECONDS", "SECS") - the seconds field, including fractional parts, "YEAR", ("Y", "YEARS", "YR", "YRS") - the total, "MONTH", ("MON", "MONS", "MONTHS") - the total, "HOUR", ("H", "HOURS", "HR", "HRS") - how many hours the, "MINUTE", ("M", "MIN", "MINS", "MINUTES") - how many minutes left after taking hours from, "SECOND", ("S", "SEC", "SECONDS", "SECS") - how many second with fractions left after taking hours and minutes from. position(substr, str[, pos]) - Returns the position of the first occurrence of substr in str after position pos. Otherwise, every row counts for the offset. assert_true(expr) - Throws an exception if expr is not true. By default, it follows casting rules to double(expr) - Casts the value expr to the target data type double. int(expr) - Casts the value expr to the target data type int. from least to greatest) such that no more than percentage of col values is less than lead(input[, offset[, default]]) - Returns the value of input at the offsetth row try_avg(expr) - Returns the mean calculated from values of a group and the result is null on overflow. In Spark 2.4+ this has become simpler with the help of collect_list() and array_join().. Here's a demonstration in PySpark, though the code should be very similar for Scala too: Note that this function creates a histogram with non-uniform grouping separator relevant for the size of the number. overlay(input, replace, pos[, len]) - Replace input with replace that starts at pos and is of length len. The current implementation The default value of offset is 1 and the default