SqlDataFrame in Expression Language: Difference between revisions

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||Unpivot (SqlDataFrame)
||Unpivot (SqlDataFrame)
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# Value column
# Value column (String)
# Name column
# Name column (String)
# Columns to unpivot
# Columns to unpivot (String array)
||
||
Performs an unpivot operation by rotating columns into rows. More information: https://docs.snowflake.com/en/sql-reference/constructs/unpivot.html.
Performs the unpivot operation for the dataframe by rotating columns into rows. More information about unpivot: https://docs.snowflake.com/en/sql-reference/constructs/unpivot.html.


Parameters:
Parameters:
# '''Value column''': Column name in the result containing the unpivotted values.
# '''Value column''': Name of the generated column in the result containing the unpivotted values.
# '''Name column''': Column name in the result containing the corresponding column names of the unpivotted values.
# '''Name column''': Name of the generated column in the result containing original column names of the unpivotted values.
# '''Columns to unpivot''': Column names in the source dataframe to be unpivotted into a single pivot column.
# '''Columns to unpivot''': Column names in the source dataframe to be unpivotted.


Note that the Unpivot function is only supported for SqlDataFrames (not in-memory DataFrames).
Note that the Unpivot function is only supported for SqlDataFrames (not in-memory DataFrames).
Example:
Example:
<pre>
<pre>
let caseAttributes = ModelById(123).CasesDatatable.SqlDataFrame;
let caseAttributes = ModelById(123).CasesDatatable;
caseAttributes.UnPivot("Value", "Case attribute", caseAttributes.ColumnTypes.Name.Where(_ != "CaseId"))
caseAttributes.SqlDataFrame.Unpivot(
  "Value",
  "Case attribute",
  caseAttributes.Columns.Where(Datatype == "String" && Name != "CaseId").Name
).Collect().toCsv()
</pre>
</pre>
|-
|-

Revision as of 10:55, 26 October 2022

SqlDataFrame represents tabular data similar to an SQL query result. Data in the SqlDataFrames are processed in the original datasource where the data is located (not in the QPR ProcessAnalyzer server memory). For each SqlDataFrame, there is an SQL query generated that is run in the datasource where the referenced datatables are located.

SqlDataFrame operations itself don't cause the SQL to execute in the datasource, but it will happen when the Collect function is called for an SqlDataFrame, which generates and executes the SQL query representing the SqlDataFrame and loads the data into QPR ProcessAnalyzer memory as a DataFrame (where it can be presented in a dashboard).

Each SqlDataFrame contain information about the datasource where the SQL query will be executed. When writing queries with several SqlDataFrames, the SqlDataFrames need to be located in the same datasource, to be able to execute the queries. If needed, data can be moved between datasources by using the Import or Persist functions. Alternatively, processing can be done in-memory by calling Collect for an SqlDataFrame and continuing calculation as in-memory DataFrame.

There is a similar API for the SqlDataFrames as there is for the DataFrames. Note that merging is not possible between SqlDataFrames like it's for DataFrames, but SqlDataFrame can be merged into a datatable.

SqlDataFrame properties Description
ColumnTypes (Dictionary)

Returns information about the columns of the SqlDataFrame as an array of dictionaries with keys Name and DataType. Columns are returned in the same order as the columns exist in the data table. Column types are calculated based on the type of the column in the relational database management system (i.e. type of the column in an SQL table).

Examples: 

table.SqlDataFrame.ColumnTypes
Returns: [ #{ "Name": "name1", "DataType": "Integer" },  #{ "Name": "name2", "DataType": "String" } ]

table.SqlDataFrame.ColumnTypes.Name
Returns: ["name1", "name2"]

table.SqlDataFrame.ColumnTypes.DataType
Returns: ["Integer", "String"]
NColumns (Integer) Returns number of columns in the dataset represented by the SqlDataFrame.
NRows (Integer) Returns number of rows in the dataset represented by the SqlDataFrame.


SqlDataFrame functions Parameters Description
Aggregate (SqlDataFrame)
  1. Aggregated columns (string array or key-value pairs)
  2. Aggregation methods (string array)
 Same functionality as in the DataFrame.
Append DataFrame to append Same functionality as in the DataFrame.
Collect (SqlDataFrame) (none)

Executes the SQL query for the SqlDataFrame in the datasource and returns results as an in-memory DataFrame. Then processing of the data can be continued as the in-memory DataFrame.

Examples: 

DataTableById(123).SqlDataFrame.Head(100).Collect().ToCsv()
Returns the top 100 rows from datatable id 123.
ExcludeValues (SqlDataFrame)
  1. Column name (string)
  2. Value (single item) or values (array) to exclude

Same functionality as in the DataFrame.

GroupBy (GroupedDataFrame)

Grouped columns (string array)

Same functionality as in the DataFrame.

Head (SqlDataFrame) Number of top rows

Same functionality as in the DataFrame.

IncludeOnlyValues (SqlDataFrame)
  1. Column name (string)
  2. Value (single item) or values (array) to include

Same functionality as in the DataFrame.

Join (SqlDataFrame)
  1. DataFrame
  2. Columns to match (String or key-value pairs)
  3. Join type (String)
 Same functionality as in the DataFrame.
OrderByColumns (SqlDataFrame)
  1. Ordered columns (String array)
  2. Sorting order (boolean array)

Same functionality as in the DataFrame.

Persist (SqlDataFrame)
  1. DataTable name
  2. Additional parameters

Same functionality as in the DataFrame. Additionally, if the SQL query for the SqlDataFrame is run in the same system as the target datatable, all data processing and storage is done within the system to achieve efficient operation.

RemoveColumns (SqlDataFrame) Column names (string array) Same functionality as in the DataFrame.
Select (SqlDataFrame) Column names (string array, or key-value pairs) Same functionality as in the DataFrame.
SelectDistinct (SqlDataFrame)

Column names (string array, or key-value pairs)

Same functionality as in the DataFrame.

Skip (SqlDataFrame) Number of rows to skip Same functionality as in the DataFrame.
TakeSample (SqlDataFrame) Number of rows (Integer) Same functionality as in the DataFrame.
Unpivot (SqlDataFrame)
  1. Value column (String)
  2. Name column (String)
  3. Columns to unpivot (String array)

Performs the unpivot operation for the dataframe by rotating columns into rows. More information about unpivot: https://docs.snowflake.com/en/sql-reference/constructs/unpivot.html.

Parameters:

  1. Value column: Name of the generated column in the result containing the unpivotted values.
  2. Name column: Name of the generated column in the result containing original column names of the unpivotted values.
  3. Columns to unpivot: Column names in the source dataframe to be unpivotted.

Note that the Unpivot function is only supported for SqlDataFrames (not in-memory DataFrames). Example: 

let caseAttributes = ModelById(123).CasesDatatable;
caseAttributes.SqlDataFrame.Unpivot(
  "Value",
  "Case attribute",
  caseAttributes.Columns.Where(Datatype == "String" && Name != "CaseId").Name
).Collect().toCsv()
WithDenseRankNumberColumn (SqlDataFrame)
  1. New column name (String)
  2. Order by columns (String array)
  3. Partition by columns (String array)
  4. Ascending/descending order (Boolean array)

Same functionality as in the DataFrame.

WithColumn (SqlDataFrame)
  1. New column name (String)
  2. New column expression

Same functionality as in the DataFrame, except instead of in-memory expressions, SqlDataFrame use SQL Expressions.

WithRankColumn (SqlDataFrame)
  1. New column name (String)
  2. Order by columns (String array)
  3. Partition by columns (String array)
  4. Ascending/descending order (Boolean array)

Same functionality as in the DataFrame.

WithRowNumberColumn (SqlDataFrame)
  1. New column name (String)
  2. Order by columns (String array)
  3. Partition by columns (String array)
  4. Ascending/descending order (Boolean array)

Same functionality as in the DataFrame.

Where (SqlDataFrame) Condition expression Same functionality as in the DataFrame, except instead of in-memory expressions, SqlDataFrame use SQL Expressions.
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