group()

@o

Group records by comparing adjacent ones, which is equal to the merging operation, and the result set won’t be sorted

@1

Get the first record of each group to form a record sequence and return it (Please note that 1 is a number instead of a letter); can work with @v option

@n

x gets assigned with group numbers which can be used to define the groups; discard groups that make x<1. @n and @0 are mutually exclusive

@u

Do not sort the result set by x. It doesn’t work with @o/@n

@i

x is a Boolean expression. If the result of x is true, then start a new group. This option is equivalent to A.group@o(a+=if(x,1,0)), in which a=0 and there is only one x

@0

Discard the group over which the result of grouping expression x is null; discard empty groups when @n is also present. Use it when there’s only one expression x

@s

Perform a concatenation of sequences/records sequences after the grouping. It is equivalent to A.group(xi,…).conj(); can work with @v option

@p

Return a sequence of integer sequences, each of which contains the positions of members in each group in sequence A

@h

Used over a grouped table with each group ordered to speed up grouping

@v

When parameter A is a pure table sequence, return a set of pure table sequences

A

A sequence

x_i

Grouping expression

A

1

[6,9,12,15,16,5,1,7,8]

2

=A1.group(~%2)

[[6,12,16,8],[ 9,15,5,1,7]] The series is divided into two groups. Divide the number of members in both groups by 2, one of the remainders is 0 and the other is 1.

3

=A1.group(~%2,~%3)

[[6,12],[16],[8],[9,15],[1,7],[5]].

Group the series according to multiple expressions.

4

=[6,9,16,5,1,7,8].group@s(~%2)

Divide the sequence into a group of odd numbers and a group of even numbers, and then concatenate them.

5

=A1.group((#-1)\3)

Group sequence A1 every 3 members.

A

1

=demo.query("select NAME,BIRTHDAY,GENDER from EMPLOYEE")

2

=A1.group(GENDER)

Group A1’s table sequence by GENDER:

[Each group is a sequence:

3

=A2.new(GENDER:Gender,~.count():Number)

Count members of each group.

4

=A2.new(GENDER:Gender,~.avg(age(BIRTHDAY)):Average)

Get different statistical results using the same grouping result.

A

1

=demo.query("select NAME,GENDER,DEPT,BIRTHDAY from EMPLOYEE")

2

=A1.group(GENDER,DEPT)

Group records by multiple fields.

3

=A1.group@o(GENDER)

Records won’t be sorted; only the adjacent ones will be compared and group them together if they match. Same records that are not adjacent may be put into different groups, so there may be overlapped groups and the returned result is a set of sequences.

4

=A1.group@1(GENDER)

Return the first record of each group.

5

=A1.group@n(if(GENDER=="F",1,2))

x gets assigned with group numbers which can be used to define the groups directly.

[[Rebecca,Ashley,Rachel,…],[Matthew,Ryan,Jacob,…]]

6

=A1.group@u(GENDER,DEPT)

Do not sort result set by the sorting field.

7

=A1.group@i(GENDER=="F")

Start a new group when GENDER=="F".

8

=A1.group@p(GENDER,DEPT)

Return a sequence of integer sequences, each of which contains the positions of records in a group (grouped by GENDER field and DEPT field) in the original table sequence.

9

=file("D:\\Salesman.txt").import@t()

10

=A9.group@0(Gender)

Group the table sequence by GENDER field, while discarding groups with null values.

11

=file("D:/emp10.txt").import@t()

For data fiel emp10.txt, every 10 records are ordered by DEPT.

12

=A11.group@h(DEPT)

As A11 is segmented and ordered by DEPT, @h option is used to speed up grouping.

13

=A1.group@n(if(DEPT=="HR":1,DEPT=="Sales":2;0))

Use @n option to discard groups of records that make the grouping expression less than 1. That is, give up those where DEPT is neither HR nor Sales.

A

1

=demo.query@v("select * from EMPLOYEE order by GENDER,DEPT ")

Return a pure table sequence.

2

=A1.group@v(GENDER,DEPT)

@v option enables returning a set of pure table sequences.

@o

Group records by comparing adjacent ones, which is equal to the merging operation, and the result set won’t be sorted

@n

x gets assigned with group numbers which can be used to define the groups. @n and @o are mutually exclusive

@u

Do not sort the result set by x. It doesn’t work with @o/@n

@i

x is a Boolean expression. If the result of x is true, then start a new group. There is only one x

@0

Discard the group over which the result of grouping expression x is null

@h

Used over a grouped table with each group ordered to speed up grouping

@t

Return an empty table sequence with data structure if the grouping and aggregate operation over the sequence returns null

@s

Summarize data cumulatively

A

A sequence

x

Grouping expression. If omitting x:F, aggregate the whole set without grouping; in this case “;” must not be omitted

F

Field name of the result table sequence

G

Names of summary fields in the result table sequence

y

Aggregate expression in which ~ is used to reference a group

A

1

=demo.query("select * from SCORES")

2

=A1.group(STUDENTID:StudentID;~.sum(SCORE):TotalScore)

3

=A1.group@o(STUDENTID:StudentID;~.sum(SCORE):TotalScore)

Only the adjacent ones will be compared and group them together if they are the same. The result set won’t be sorted.

4

=demo.query("select * from STOCKRECORDS where STOCKID<'002242'")

5

=A4.group@n(if(STOCKID=="000062",1,2):StockID;~.sum(CLOSING):TotalPrice)

x gets assigned with group numbers.

6

=A1.group(;~.sum(SCORE):TotalScore)

Parameters x:F are omitted, so compute the total score of all the students.

7

=demo.query("select * from EMPLOYEE")

8

=A7.group@u(STATE:State;~.count(STATE):TotalScore)

Do not sort result set by the sorting field.

9

=A7.group@i((GENDER=="F"):IsF;~.count():Number)

Start a new group when GENDER=="F".

10

=file("D:\\Salesman.txt").import@t()

11

=A10.group@0(Gender:Gender;~.sum(Age):Total)

Discard the groups where GENDER values are null.

12

=file("D:/emp10.txt").import@t()

For data file emp10.txt, every 10 records are ordered by DEPT

13

=A12.group@h(DEPT:dept;~.sum(SALARY):bouns)

As A12 are segmented and ordered by DEPT, @h option is used to speed up grouping.

14

=demo.query("select * from EMPLOYEE where EID > 500")

Return an empty table sequence.

15

=A14.group@t(STATE:State;~.count(STATE):TotalScore)

Return an empty table sequence with the data structure.

16

=demo.query("select * from employee").group@s(DEPT;sum(SALARY):TotalSalary)

Perform aggregation cumulatively.

@i

With this option and with grouping expression x being a Boolean expression, start a new group if the result of x is true. Be sure there’s only one x in this case

@1

Get the first record of every group to form a record sequence and return it to the original channel (here it is number 1 rather than letter l)

ch

A channel

x

Grouping expression

A

1

=demo.cursor("select EID,GENDER,DEPT,NAME,SALARY from EMPLOYEE").sortx(GENDER,DEPT)

Return a cursor ordered by by GENDER and DEPT fields.

2

=channel()

Create a channel.

3

=A2.group(GENDER,DEPT)

Attach a computation to channel A2, which will group its records by GENDER and DEPT.

4

=A2.fetch()

Execute the result set function in channel A2 and keep the current data in channel.

5

=A1.push(A2)

Be ready to push cursor A1’s data to channel A2, but the action needs to wait.

6

=A1.skip()

Fetch data from cursor A1 while pushing data into the channel to execute the attached computation and keep the result.

7

=A2.result()

Get channel A2’s result:

A

1

=demo.cursor("select EID,GENDER,DEPT,NAME,SALARY from EMPLOYEE").sortx(DEPT)

Return a cursor ordered by DEPT field

2

=channel()

Create a channel.

3

=channel()

Create a channel.

4

=A2.group@1(DEPT)

Attach a computation to channel A2, which will group its records by DEPT field and use @1 option to get the first record of every group to form a record sequence, and return the original channel A2.

5

=A2.fetch()

Execute the result set function in channel A2 and keep the current data in channel.

6

=A3.group@i(GENDER=="F")

Attach a computation to channel A3, which will group its records by DEPT field and use @i option to create a new group whenever DEPT =="HR" is met, and return the original channel A3.

7

=A3.fetch()

Execute the result set function in channel A3 and keep the current data in channel.

8

=A1.push(A2,A3)

Be ready to push the data in A1’s cursor to channels A2 and A3, but the action needs to wait.

9

=A1.skip()

Fetch data from cursor A1 while pushing data into the channel to execute the attached computation and keep the result.

10

=A2.result()

Get channel A2’s result:

11

=A3.result()

Get channel A3’s result:

@i

x is a Boolean expression. Begin a new group when a record makes it return true. In this case there should be only one x

@1

Get the first record of every group to form a record sequence and return it to the original cursor; here it is number 1 instead of letter l

@v

When parameter cs is a cursor based on pure table sequence, copy each grouped subset as a new pure table sequence

cs

A cursor or multicursor

x

Grouping expression

A

1

=demo.cursor("select * from EMPLOYEE").sortx(GENDER,DEPT)

Return a cursor where data is ordered by GENDER and DEPT.

2

=A1.group(GENDER,DEPT)

Attach a computation to cursor A1, which puts records in the same group when two neighboring records have same GENDER and DEPT values, and return the original cursor.

3

=A1.fetch()

Fetch data from cursor A1 where A2’s computation is executed (fetch data in batches when there is a huge amount of data):

A

1

=demo.cursor("select * from STOCKRECORDS where STOCKID='000062' ").sortx(DATE)

Return a cursor where data is ordered by DATE.

2

=A1.group@i(CLOSING<CLOSING[-1])

Attach a computation to cursor A1, which, with @i option, creates a new group whenever CLOSING value in the current record is less than that in the previous record, and return the original cursor.

3

=A1.fetch()

Fetch data from cursor A1 where A2’s computation is executed:

A

1

=demo.cursor("select EID,NAME,DEPT,HIREDATE from EMPLOYEE").sortx(DEPT,HIREDATE)

Return a cursor where data is ordered by DEPT and HIREDATE.

2

=A1.group@1 (DEPT)

Attach a computation to cursor A1, which, with @1 option, groups records in the cursor by DEPT and gets the first record in each group, and return the original cursor.

3

=A1.fetch()

Fetch data from cursor A1 where A2’s computation is executed:

A

1

=demo.cursor@v("select * from EMPLOYEE order by GENDER,DEPT")

Return a cursor of pure table sequence.

2

=A1.group@v(GENDER,DEPT)

Attach a computation to cursor A1, which, with @v option, copies each grouped subset as a new pure table sequence, and return the original cursor.

3

=A1.fetch()

Get the number of groups in cursor A1 where A2’s computation is executed.

cs

A cluster cursor

x

Grouping expression; use comma to separate multiple grouping fields or expressions

A

1

=file("employees.ctx","192.168.0.111:8281")

Below is employees.ctx ordered by DEPT field:

2

=A1.open()

Create a cluster composite table.

3

=A2.cursor()

Return a cluster cursor.

4

=A3.group(DEPT)

Group the cluster cursor by DEPT and return the grouped cluster cursor.

5

=A4.fetch()

cs

A cursor

x

Grouping expression

F

Field name

G

Aggregation field name

y

Aggregate expression

@s

Cumulative aggregation

@q(x:F,…;x’:F’,…; y:G,…)

Used when parameter cs is ordered by x,… and only fields after it need to be sorted; support in-memory sorting

@sq(x:F,…;x’:F’,…; y:G,…)

Only sort without grouping when parameters y:G are absent, and perform cumulative aggregation when the parameters are present; @s works only when @q option is present

@e

Return a table sequence consisting of results of expression y to the original cursor; grouping expression x is a field of cs and y is function on cs; the result of computing y must be one record of cs; and y only supports maxp, minp and top@1 functions when it is an aggregate expression;

When @sev options work together, the function returns a pure table sequence

A

1

=demo.cursor("select * from SCORES").sortx(CLASS,STUDENTID)

Return a cursor whose data is ordered by CLASS and STUDENTID fields; below is the content:

2

=A1.group(CLASS:Class,STUDENTID:StudentID;~.sum(SCORE):TotalScore)

Attach a computation to cursor A1, which groups records in the cursor by comparing neighboring CLASS and STUDENTID values and computes total scores, which are made TotalScore field values, in each group, and return the original cursor.

3

=A1.fetch()

Fetch data from cursor A1 where A2’s computation is executed:

A

1

=demo.cursor("select EID,NAME,DEPT,GENDER,SALARY from EMPLOYEE ").sortx(DEPT)

Return a cursor whose data is ordered by DEPT field; below is the content:

2

=A1.group@q(DEPT;GENDER;~.avg(SALARY):Avg_Salary)

Attach a computation to cursor A1 that is ordered by DEPT and where only GENDER field needs to be ordered; @q option is used to enable an in-memory sorting, and return the original cursor.

3

=A1.fetch()

Fetch data from cursor A1 where A2’s computation is executed:

A

1

=demo.cursor("select EID,NAME,DEPT,GENDER,SALARY from EMPLOYEE ").sortx(DEPT)

Return a cursor whose data is ordered by DEPT field; below is the content:

2

=A1.group@sq(DEPT;GENDER)

Attach a computation to cursor A1 ordered only by DEPT; here the function does not specify the aggregate parameter is absent and use @sq options to sort without grouping, and returns the original cursor.

3

=A1.fetch()

Fetch data from cursor A1 where A2’s computation is executed:

A

1

=demo.cursor("select EID,NAME,DEPT,SALARY from EMPLOYEE  ").sortx(DEPT)

Return a cursor whose data is ordered by DEPT field; below is the content:

2

=A1.group@e(DEPT;~.maxp(SALARY))

Attach a computation to cursor A1; the function work with @e option to return the result records of computing maxp(SALARY) to the original cursor.

3

=A1.fetch()

Fetch data from cursor A1 where A2’s computation is executed:

cs

A cluster cursor

x

Grouping expression

F

Field name

G

Field to be aggregated

y

Aggregation expression

A

1

=file("employees.ctx","192.168.0.111:8281")

employees.ctx is ordered by DEPT. Its content is as follows:

2

=A1.open()

Open the cluster composite table.

3

=A2.cursor()

Return a cluster cursor.

4

=A3.group(DEPT:dept;count(NAME):count)

Group records by DEPT and perform aggregation on each group and return result to the original cluster cursor.

5

=A4.fetch()

T

A pseudo table

x_i

Grouping expression; use comma to separate multiple grouping fields or expressions

@i

x is a Boolean expression. Begin a new group when a record makes it return true. In this case there should be only one x

@1

Get the first record of every group to form a record sequence and return it; here it is number 1, instead of letter l

@v

Store the composite table in the column-wise format when loading it the first time, which helps to increase performance

A

1

=create(file).record(["D:/file/pseudo/empT.ctx"])

2

=pseudo(A1)

Generate a pseudo table object, whose data is as follows:

3

=A2.group(GENDER,DEPT)

Define a computation on A2’s pseudo table, which will put records where both GENDER and DEPT values are same into the same group, and return a new pseudo table.

4

=A3.import()

Import data from A3’s pseudo table while executing the computation in A3 defined on A2’s pseudo table, and return the following pseudo table:

5

=A2.group@i(GENDER=="F")

With @i option, create a new group whenever the record meets the condition GENDER=="F".

6

=A5.import()

Get data from A5’s pseudo table.

7

=A2.group@1(GENDER)

With @1 option, return the first record of each group.

8

=A7.cursor().fetch()

Fetch data from A7’s pseudo table:

T

A pseudo table

x

Grouping expression

F

Field name

G

Aggregation field name

y

Aggregate expression

@s

Cumulative aggregation

@q(x:F,…;x’:F’,…;…)

Used when parameter T is ordered by x,… and only fields after it need to be sorted; support in-memory sorting

@sq(x:F,…;x’:F’,…;…)

Only sort without grouping when parameters y:G are absent, and perform cumulative aggregation when the parameters are present; @s works only when @q option is present

@e

Return a pseudo table consisting of results of expression y; grouping expression x is a field of T and y is function on T; the result of computing y must be one record of T; and y only supports maxp, minp and top@1 functions when it is an aggregate expression

A

1

=create(file).record(["scores-g.ctx"])

scores-g.ctx is a composite table file ordered by STUDENTID; its content is as follows:

2

=pseudo(A1)

Generate a pseudo table from composite table A1.

3

=A2.group(STUDENTID:StudentID;~.sum(SCORE):TotalScore)

Define a computation on A2’s pseudo table, which will group pseudo table A2 by STUDENTID and compute total SCORE values in each group, and return a new pseudo table.

4

=A3.import()

Import data from A3’s pseudo table while executing the computation defined on A2’s pseudo table in A3, and return the following pseudo table:

A

1

=create(file).record(["emp-g.ctx"])

emp-g.ctx is a composite table file ordered by DEPT; its content is as follows:

2

=pseudo(A1)

Generate a pseudo table from composite table A1.

3

=A2.group@q(DEPT;GENDER)

Define a computation on A2’s pseudo table – as the pseudo table is already ordered by DEPT, the function only sorts by GENDER during grouping – and return a new pseudo table:

4

=A3.cursor().fetch()

Fetch data from A3’s pseudo table while executing the computation defined on A2’s pseudo table in A3, and return the following pseudo table:

5

=A2.group@qs(DEPT:DEPT;GENDER:GENDER)

Define a computation on A2’s pseudo table, which will only sort records without grouping since parameters y:G are absent, and return a new pseudo table.

6

=A5.import()

Import data from A5’s pseudo table while executing the computation defined on A2’s pseudo table in A5, and return the following pseudo table:

7

=A2.group@qs(DEPT:DEPT;GENDER:GENDER;count(GENDER):count)

Define a computation on A2’s pseudo table, which will Perform cumulative aggregation as parameters y:G are present, and return a new pseudo table.

8

=A7.import()

Import data from A7’s pseudo table while executing the computation defined on A2’s pseudo table in A7, and return the following pseudo table:

A

1

=create(file).record(["emp-g.ctx"])

Below is content of composite table emp-g.ctx:

2

=pseudo(A1)

Generate a pseudo table from composite table A1.

3

=A2.group@e(DEPT;~.minp(SALARY))

Define a computation on A2’s pseudo table, which, with @e option, will return a pseudo table consisting of result records of computing minp(SALARY).

4

=A3.fetch().cursor()

Fetch data from A3’s pseudo table while executing the computation defined on A2’s pseudo table in A3, and return the following pseudo table: