Iterative SQL Mapping#
iterativeSql mapping allows to iteratively execute SQL transformation which contains Spark SQL code. The
iteration will stop when the data does not change anymore.
The following example will detect trees within a company hierarchy table, which provides simple parent-child
relations. The objective of the query is to assign a separate ID to each company tree. The query will essentially
tree_id from each parent down to its direct children. This step is performed over and over again
tree_id from the root companies without a parent are propagated to the leave companies without any
mappings: organization_hierarchy: kind: iterativeSql input: companies sql: | SELECT COALESCE(parent.tree_id, c.tree_id) AS tree_id, c.parent_company_number, c.company_number FROM companies c LEFT JOIN __this__ parent ON c.parent_company_number = parent.company_number
Within the first step, the output of the input mapping
companies is assigned to the identifier
__this__. Then the
SQL query is executed for the first time, which will provide the start value of the forthcoming iteration. In each
iteration, the result of the previous iteration is assigned to
__this__ and the query is executed.
Then the result is compared to the result of the previous iteration. If the results are the same, a fix point is
reached and the execution stops. Otherwise, the iteration will continue.
kind(mandatory) (type: string):
broadcast(optional) (type: boolean) (default: false): Hint for broadcasting the result of this mapping for map-side joins.
cache(optional) (type: string) (default: NONE): Cache mode for the results of this mapping. Supported values are
NONE- Disables caching of teh results of this mapping
DISK_ONLY- Caches the results on disk
MEMORY_ONLY- Caches the results in memory. If not enough memory is available, records will be uncached.
MEMORY_ONLY_SER- Caches the results in memory in a serialized format. If not enough memory is available, records will be uncached.
MEMORY_AND_DISK- Caches the results first in memory and then spills to disk.
MEMORY_AND_DISK_SER- Caches the results first in memory in a serialized format and then spills to disk.
input(required) (type: string): The input mapping which serves as the starting point of the iteration. This means that for the first execution, the identifier
__this__will simply refer the output of this mapping. Within the next iterations,
__this__will refer to the result of the previous iteration.
sql(optional) (type: string) (default: empty): The SQL statement to execute
file(optional) (type: string) (default: empty): The name of a file containing the SQL to execute.
uri(optional) (type: string) (default: empty): A URL pointing to a resource containing the SQL to execute.
maxIterations(optional) (type: int) (default: 99): The maximum of iterations. The mapping will fail if the number of actual iterations required to find the fix point exceeds this number.
main- the only output of the mapping
iterativeSql mapping allows executing recursive SQL statements, which refer to themselves.
Flowman also supports
recursiveSql mappings, which provide similar functionality more along
the lines of classical recursive SQL statements.