2.00.12

Introduced a change regarding the permissions for shell function calls by administrators:

• In previous release, there is no restriction for administrators to call the shell function.

• Since this release, calling shell functions is not allowed for any user by default, including administrators. To call the shell function, you must set the configuration parameter enableShellFunction to true.

• Changed the rounding behavior when converting floating-point number to DECIMAL type from truncation to rounding.

  decimal128(0.000009,5)
  // Output (previous releases): 0.00000
  // Output (current release): 0.00001

• Modified asof join with multiple join columns if the left or right table is a partitioned table and the first (n-1) join columns did not include all partitioning columns:

  • In previous releases, the join operation was allowed.

  • Since this release, an error is thrown.

  // Create partitioned tables pt1 and pt2
  if(existsDatabase("dfs://aj_test")) dropDatabase("dfs://aj_test")
  db=database("dfs://aj_test", VALUE, 2023.01M..2024.01M, engine='TSDB')
  
  sym=take(`a`b, 20)
  date=2023.01.01 + (1..20) * 5
  value= rand(10.0, 20)
  t1 = table(sym, date, value)
  
  sym=take(`a`b, 20)
  date=2023.01.02 + (1..20) * 5
  price= rand(10.0, 20)
  t2 = table(sym, date, price)
  
  pt1 = db.createPartitionedTable(t1, "pt1", `date, sortColumns=`sym`date).append!(t1)
  pt2 = db.createPartitionedTable(t2, "pt2", `date, sortColumns=`sym`date).append!(t2)
  
  // asof join on pt1 and pt2
  select * from aj(pt1, pt2, `sym`date)
  
  // Previous releases returned the join result
  // Current release throws an error: In asof join (aj), if the left or right table is a partitioned table, the matching columns except the last one must include all partitioning columns.

• In previous releases, passing a 0-column matrix to an aggregate or vector function was allowed. Since this release, an error is thrown.

  input=matrix(INT,1,0)
  valueChanged(input)
  
  // Previous releases returned the result
  // Current release throws an error: The column number of matrix must be greater than 0.

• Behavior change of function at(X, [index]) when X is a function and index is a tuple:

  • In previous releases, the tuple was passed as an argument to X.

  • Since this release, each element of the tuple is passed as an argument to X.

  def myFunc(x, y=10){
      return x+y
  }
  at(myFunc, (1,2))
  
  // Output (previous releases): (11,12)
  // Output (current release): 3

  To replicate previous behavior, nest the tuple as the only element within another tuple before passing the argument. For example:

  def myFunc(x, y=10){
      return x+y
  }
  at(myFunc, ().append!((1,2)))
  // Output: (11,12)

• In previous releases, the SQL predicate IN could access columns in DFS tables. Since this release, such columns can only be accessed using a subquery.

  // create DFS tables
  if(existsDatabase("dfs://in_test")){
  	dropDatabase("dfs://in_test")
  }
  db=database("dfs://in_test", VALUE, 1..10,,'TSDB')
  t1=table([1 ,1, 2 ,2] as id, "A"+string(1..4) as sym, rand(10.0,4) as val)
  t2=table([1 ,1, 2 ,3] as uid, "A"+string(1..4) as sym, rand(10.0,4) as val)
  pt1=db.createPartitionedTable(t1, `pt1,`id,,`sym).append!(t1)
  pt2=db.createPartitionedTable(t2, `pt2,`uid,,`sym).append!(t2)
  
  // Query
  select * from pt1 left join pt2 on pt1.id ==pt2.uid where pt1.id in (case when pt1.sym="A1" then 1 end)
  
  // Previous releases returned query results
  // Current release reports an error: The '[not] in' predicate cannot be followed by columns from the partitioned table. Please use a subquery instead.
  // Use a subquery
  select * from pt1 left join pt2 on pt1.id ==pt2.uid where pt1.id in (select case when sym="A1" then 1 end from pt1)

• Modified the behavior of functions milastNot, mifirstNot,mimax, mimin, mfirstNot, mlastNot, mifirstNot, milastNot, mimaxLast, miminLast if X is an indexed series or indexed matrix.

  • When the index contains NULL values, previous releases allowed such operation, while an error is reported since this release.

    data = indexedSeries(NULL 2014.01.12 2014.01.13 2014.01.14 2014.01.15 2014.01.16, 1..6)
    milastNot(data, 4)
    
    // Output (previous releases):
    
    label	col1
    	
    2014.01.12	
    2014.01.13	
    2014.01.14	3
    2014.01.15	3
    2014.01.16	3
    
    // Output (current release): The row index of the matrix can't contain null if window is a time offset.

  • In previous releases, these functions slided a window by row, which was inconsistent with the time-based windowing logic for indexed data forms. The current release fixes this issue.

    data = indexedSeries(2014.01.11 2014.01.12 2014.01.13 2014.01.14 2014.01.15 2014.01.16, 1 NULL 3 NULL 4 5)
    milastNot(data, 4)
    
    // Output (previous releases):
    label	col1
    2014.01.11	
    2014.01.12	
    2014.01.13	
    2014.01.14	2
    2014.01.15	3
    2014.01.16	3
    
    // Output (current release):
    label	col1
    2014.01.11	0
    2014.01.12	0
    2014.01.13	2
    2014.01.14	2
    2014.01.15	3
    2014.01.16	3