This document describes how to flatten hierarchical employee data stored in an Oracle database table into normalized columns using a single SQL query. It involves using SYS_CONNECT_BY_PATH to concatenate the employee names and roles into path strings, extracting the levels using regular expressions, and pivoting the results into columns labeled by role (e.g. "PROJECT_MANAGER", "DBA", etc.) using DECODE. The technique allows flattening of hierarchical data without complex joins or recursion.

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A single Oracle SQL can find the entire tree of data above or below a node in a hierarchy using the
CONNECT BY clause.
What if the requirement is to flatten hierarchical data?
For example, given a table containing the employee reporting hierarchy of an organization (image
alongside), get a single SQL to return the 4 types of employee roles as columns:
 PROJECT_MANAGER (Level 1)
 DBA (Level 2)
 TEAM_LEAD (Level 2)
 TEAM_MEMBER (Level 3)
This is trickier than transposing rows as columns in a non-hierarchical table, and needs a little extra
to get the result. But it is nowhere near as tough as it appears. No multiple self-joins, no recursive
CTE.
This post will show you how to flatten hierarchical data using a single SQL in Oracle.
To build the SQL, let’s populate the hierarchical table EMPL with some data, as
below.
Simple SELECT on the data:
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SQL> -- Data in EMPL table
SQL> select * from empl;
EMP_NAME EMP_ROLE MANAGER_EMP_NA
---------------- --------------- --------------

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Peter Matthews PROJECT_MANAGER
Tom Ledford TEAM_LEAD Peter Matthews
Timothy Leigh TEAM_LEAD Peter Matthews
David Botham DBA Peter Matthews
Trevor Malcolm TEAM_MEMBER Tom Ledford
Toby Mayer TEAM_MEMBER Tom Ledford
Trevor McDermott TEAM_MEMBER Timothy Leigh
Thor Martin TEAM_MEMBER Timothy Leigh
9 rows selected.
The expected result:
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PROJECT_MANAGER DBA TEAM_LEAD TEAM_MEMBER
--------------- --------------- --------------- ---------------
Peter Matthews
Peter Matthews Tom Ledford
Peter Matthews Tom Ledford Trevor Malcolm
Peter Matthews Tom Ledford Toby Mayer
Peter Matthews Timothy Leigh
Peter Matthews Timothy Leigh Trevor McDermott
Peter Matthews Timothy Leigh Thor Martin
Peter Matthews David Botham
We get to the expected result using a combination of SYS_CONNECT_BY_PATH and regular
expressions.
The Magic SQL
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SQL> select emplevel1 project_manager
2 , decode(rolelevel2, 'DBA', emplevel2) dba
3 , decode(rolelevel2, 'TEAM_LEAD', emplevel2) team_lead
4 , emplevel3 team_member
5 from
6 (
7 select
8 regexp_substr(role_path, '[^/]+', 1, 1) rolelevel1
9 , regexp_substr(emp_path, '[^/]+', 1, 1) emplevel1
10 , regexp_substr(role_path, '[^/]+', 1, 2) rolelevel2
11 , regexp_substr(emp_path, '[^/]+', 1, 2) emplevel2
12 , regexp_substr(role_path, '[^/]+', 1, 3) rolelevel3
13 , regexp_substr(emp_path, '[^/]+', 1, 3) emplevel3
14 from
15 (
16 select
17 sys_connect_by_path (emp_role, '/') role_path
18 , sys_connect_by_path (emp_name, '/') emp_path
19 from empl
20 start with manager_emp_name is null

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21 connect by prior
22 emp_name = manager_emp_name
23 )
24 );
PROJECT_MANAGER DBA TEAM_LEAD TEAM_MEMBER
--------------- --------------- --------------- ---------------
Peter Matthews
Peter Matthews Tom Ledford
Peter Matthews Tom Ledford Trevor Malcolm
Peter Matthews Tom Ledford Toby Mayer
Peter Matthews Timothy Leigh
Peter Matthews Timothy Leigh Trevor McDermott
Peter Matthews Timothy Leigh Thor Martin
Peter Matthews David Botham
8 rows selected.
Making Sense of That SQL
1. The first step is to concatenate hierarchical data in a single “/”-delimited string. This gives us:
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SQL>-- Concatenate hierarchical data
SQL>-- in a single /-delimited string
SQL>select
2 sys_connect_by_path (emp_role, '/') role_path
3 , sys_connect_by_path (emp_name, '/') emp_path
4 from empl
5 start with manager_emp_name is null
6 connect by prior
7 emp_name = manager_emp_name;
ROLE_PATH EMP_PATH
-------------------------------------- -----------------------------------------
/PROJECT_MANAGER /Peter Matthews
/PROJECT_MANAGER/TEAM_LEAD /Peter Matthews/Tom Ledford
/PROJECT_MANAGER/TEAM_LEAD/TEAM_MEMBER /Peter Matthews/Tom Ledford/Trevor Malcolm
/PROJECT_MANAGER/TEAM_LEAD/TEAM_MEMBER /Peter Matthews/Tom Ledford/Toby Mayer
/PROJECT_MANAGER/TEAM_LEAD /Peter Matthews/Timothy Leigh
/PROJECT_MANAGER/TEAM_LEAD/TEAM_MEMBER /Peter Matthews/Timothy Leigh/Trevor McDermott
/PROJECT_MANAGER/TEAM_LEAD/TEAM_MEMBER /Peter Matthews/Timothy Leigh/Thor Martin
/PROJECT_MANAGER/DBA /Peter Matthews/David Botham
9 rows selected.

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So employee names are concatenated in order of reporting hierarchy, as emp_path =
emp1/emp2/…/empN, where 1 is the topmost node in the hierarchy. Similarly, the reporting path is
role_path = role1/role2/…/roleN
2. Next, separate out the elements from the string using regular expressions. The Nth match of “/” in
the strings role_path and emp_path finds the values for text in rolelevelN and emplevelN.
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SQL> -- Regexp to separate out discrete roles and
SQL> -- employees, by level
SQL> select
2 regexp_substr(role_path, '[^/]+', 1, 1) rolelevel1
3 , regexp_substr(emp_path, '[^/]+', 1, 1) emplevel1
4 , regexp_substr(role_path, '[^/]+', 1, 2) rolelevel2
5 , regexp_substr(emp_path, '[^/]+', 1, 2) emplevel2
6 , regexp_substr(role_path, '[^/]+', 1, 3) rolelevel3
7 , regexp_substr(emp_path, '[^/]+', 1, 3) emplevel3
8 from
9 (
10 -- Concatenate hierarchical data
11 -- in a single /-delimited string
12 select
13 sys_connect_by_path (emp_role, '/') role_path
14 , sys_connect_by_path (emp_name, '/') emp_path
15 from empl
16 start with manager_emp_name is null
17 connect by prior
18 emp_name = manager_emp_name
19 );
ROLELEVEL1 EMPLEVEL1 ROLELEVEL2 EMPLEVEL2 ROLELEVEL3 EMPLEVEL3
--------------- --------------- ---------- ------------- ----------- ----------------
PROJECT_MANAGER Peter Matthews
PROJECT_MANAGER Peter Matthews TEAM_LEAD Tom Ledford
PROJECT_MANAGER Peter Matthews TEAM_LEAD Tom Ledford TEAM_MEMBER Trevor Malcolm
PROJECT_MANAGER Peter Matthews TEAM_LEAD Tom Ledford TEAM_MEMBER Toby Mayer
PROJECT_MANAGER Peter Matthews TEAM_LEAD Timothy Leigh
PROJECT_MANAGER Peter Matthews TEAM_LEAD Timothy Leigh TEAM_MEMBER Trevor McDermott
PROJECT_MANAGER Peter Matthews TEAM_LEAD Timothy Leigh TEAM_MEMBER Thor Martin
PROJECT_MANAGER Peter Matthews DBA David Botham
8 rows selected.
In this data set, we have a decision to make at Level 2, since the DBA as well as the TEAM_LEAD
report to the PROJECT_MANAGER. Level 1 can always be taken as PROJECT_MANAGER, Level 3
as TEAM_MEMBER.

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As with PIVOT queries on non-hierarchical data, here too we need to be sure that the column
headers of flattened data are fixed.
3. Finally, make an inline view of the SQL above, and DECODE on rolelevelN to choose the right
column headers.
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SQL> -- Transposed columns by rolelevelN
SQL> select emplevel1 project_manager
2 , decode(rolelevel2, 'DBA', emplevel2) dba
3 , decode(rolelevel2, 'TEAM_LEAD', emplevel2) team_lead
4 , emplevel3 team_member
5 from
6 (
7 -- Regexp to separate out discrete roles and
8 -- employees, by level
9 select
10 regexp_substr(role_path, '[^/]+', 1, 1) rolelevel1
11 , regexp_substr(emp_path, '[^/]+', 1, 1) emplevel1
12 , regexp_substr(role_path, '[^/]+', 1, 2) rolelevel2
13 , regexp_substr(emp_path, '[^/]+', 1, 2) emplevel2
14 , regexp_substr(role_path, '[^/]+', 1, 3) rolelevel3
15 , regexp_substr(emp_path, '[^/]+', 1, 3) emplevel3
16 from
17 (
18 -- Concatenate hierarchical data
19 -- in a single /-delimited string
20 select
21 sys_connect_by_path (emp_role, '/') role_path
22 , sys_connect_by_path (emp_name, '/') emp_path
23 from empl
24 start with manager_emp_name is null
25 connect by prior
26 emp_name = manager_emp_name
27 )
28 );
PROJECT_MANAGER DBA TEAM_LEAD TEAM_MEMBER
--------------- --------------- --------------- ---------------
Peter Matthews
Peter Matthews Tom Ledford
Peter Matthews Tom Ledford Trevor Malcolm
Peter Matthews Tom Ledford Toby Mayer
Peter Matthews Timothy Leigh
Peter Matthews Timothy Leigh Trevor McDermott
Peter Matthews Timothy Leigh Thor Martin
Peter Matthews David Botham
8 rows selected.

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