for further mucking with data. This can be of use in ill situations
where not all the required massaging can be done on data with SQL
by means of stored procedures, but overlays are called too early
and cannot be used to make data non LDAP compliant.
- only support for bidirectional DN mucking is provided right now
- support for other values mucking is planned
- write is not completely tested yet
- the API could change quite often; don't rely too much on it
other cleanup has been added.
Now related ITSes need be audited and possibly closed.
Enhancements:
- re-styled code for better readability
- upgraded backend API to reflect recent changes
- LDAP schema is checked when loading SQL/LDAP mapping
- AttributeDescription/ObjectClass pointers used for more efficient
mapping lookup
- bervals used where string length is required often
- atomized write operations by committing at the end of each operation
and defaulting connection closure to rollback
- added LDAP access control to write operations
- fully implemented modrdn (with rdn attrs change, deleteoldrdn,
access check, parent/children check and more)
- added parent access control, children control to delete operation
- added structuralObjectClass operational attribute check and
value return on search
- added hasSubordinate operational attribute on demand
- search limits are appropriately enforced
- function backsql_strcat() has been made more efficient
- concat function has been made configurable by means of a pattern
- added config switches:
- fail_if_no_mapping write operations fail if there is no mapping
- has_ldapinfo_dn_ru overrides autodetect
- concat_pattern a string containing two '?' is used
(note that "?||?" should be more portable
than builtin function "CONCAT(?,?)")
- strcast_func cast of string constants in "SELECT DISTINCT statements (needed by PostgreSQL)
- upper_needs_cast cast the argument of upper when required
(basically when building dn substring queries)
Todo:
- add security checks for SQL statements that can be injected (?)
- re-test with previously supported RDBMs
- replace dn_ru and so with normalized dn (no need for upper() and so
in dn match)
- implement a backsql_normalize() function to replace the upper()
conversion routines
- note that subtree deletion, subtree renaming and so could be easily
implemented (rollback and consistency checks are available :)
- implement "lastmod" and other operational stuff (ldap_entries table ?)
- now all write operations appear to work correctly with PostgeSQL 7.0
- all write operations have been made transactional (atomic writes to
entries are committed separately only in case of complete^1 success
while all other operations are rolled-back by default)
- more cleanup and handling of exceptional conditions
TODO:
- deen to check with different databases and more up to date versions
of both unixODBC and PostgreSQL.
^1: attribute add/modify/delete operations silently succeed if the
appropriate add/delete proc does not exist for each attribute;
this may be correct to hide undesired/unimplemented correspondence
between LDAP and SQL databases; however, a more appropriate
LDAP behavior would be a failure with LDAP_UNAVAILABLE if a
single write operation cannot be executed for such reason
- re-style according to the style giudelines for better readability
- updated to recent frontend/backend API changes
- fixed a few quirks about normalization
- "optimized" a few memory allocation/string handling functions
- fixed a few quirks about add/modify (still have to look ad modrdn)
todo:
- there is still something broken (at least with PostgreSQL and IBM db2,
the two RDBMS O have at hand) when adding
- move everything to struct bervals and try to save a few strlen
- try some LDAP/SQL syntax relation to use appropriate value bind if possible
- ...
Summary of changes is cited below.
The patch still needs some cosmetic changes to be made, but is ready for testing.
-----Original Message-----
From: Sam Drake [mailto:drake@timesten.com]
Sent: Saturday, April 07, 2001 10:40 PM
To: 'mitya@seismic.ru'
Cc: openldap-devel@OpenLDAP.org
Subject: RE: Slapd frontend performance issues
FYI, here is a short description of the changes I made. I'll package up the
changes asap, but it may take a couple of days.
The performance numbers quoted in this report were seen at my location with
a 100,000 object database ... the slower numbers I mentioned earlier were
reported by a customer with a 1,000,000 object database.
I also can't explain the very poor performance I saw with OpenLDAP and LDBM
with a 100,000 object database.
...Sam Drake / TimesTen Performance Software
----------
Work Performed
OpenLDAP 2.0.9, including back-sql, was built successfully on Solaris
8 using gcc. The LDAP server itself, slapd, passed all tests bundled
with OpenLDAP. OpenLDAP was built using Sleepycat LDBM release 3.1.17
as the "native" storage manager.
The experimental back-sql facility in slapd was also built
successfully. It was built using Oracle release 8.1.7 and the Oracle
ODBC driver and ODBC Driver Manager from Merant. Rudimentary testing
was performed with the data and examples provided with back-sql, and
back-sql was found to be functional.
Slapd and back-sql were then tested with TimesTen, using TimesTen
4.1.1. Back-sql was not immediately functional with TimesTen due to a
number of SQL limitations in the TimesTen product.
Functional issues encountered were:
1. Back-sql issued SELECT statements including the construct,
"UPPER(?)". While TimesTen supports UPPER, it does not support the
use of parameters as input to builtin functions. Back-sql was
modified to convert the parameter to upper case prior to giving it
to the underlying database ... a change that is appropriate for all
databases.
2. Back-sql issued SELECT statements using the SQL CONCAT function.
TimesTen does not support this function. Back-sql was modified to
concatentate the necessary strings itself (in "C" code) prior to
passing the parameters to SQL. This change is also appropriate for
all databases, not just TimesTen.
Once these two issues were resolved, back-sql could successfully
process LDAP searches using the sample data and examples provided with
back-sql.
While performance was not measured at this point, numerous serious
performance problems were observed with the back-sql code and the
generated SQL. In particular:
1. In the process of implementing an LDAP search, back-sql will
generate and execute a SQL query for all object classes stored in
back-sql. During the source of generating each SQL query, it is
common for back-sql to determine that a particular object class can
not possibly have any members satisfying the search. For example,
this can occur if the query searches an attribute of the LDAP
object that does not exist in the SQL schema. In this case,
back-sql would generate and issue the SQL query anyway, including a
clause such as "WHERE 1=0" in the generated SELECT. The overhead
of parsing, optimizing and executing the query is non-trivial, and
the answer (the empty set) is known in advance. Solution: Back-sql
was modified to stop executing a SQL query when it can be
predetermined that the query will return no rows.
2. Searches in LDAP are fundamentally case-insensitive ("abc" is equal
to "aBc"). However, in SQL this is not normally the case.
Back-sql thus generated SQL SELECT statements including clauses of
the form, "WHERE UPPER(attribute) = 'JOE'". Even if an index is
defined on the attribute in the relational database, the index can
not be used to satisfy the query, as the index is case sensitive.
The relational database then is forced to scan all rows in the
table in order to satisfy the query ... an expensive and
non-scalable proposition. Solution: Back-sql was modified to allow
the schema designer to add additional "upper cased" columns to the
SQL schema. These columns, if present, contain an upper cased
version of the "standard" field, and will be used preferentially
for searching. Such columns can be provided for all searchable
columns, some columns, or no columns. An application using
database "triggers" or similar mechanisms can automatically
maintain these upper cased columns when the standard column is
changed.
3. In order to implement the hierarchical nature of LDAP object
hierarchies, OpenLDAP uses suffix searches in SQL. For example, to
find all objects in the subtree "o=TimesTen,c=us", a SQL SELECT
statement of the form, "WHERE UPPER(dn) LIKE '%O=TIMESTEN,C=US'"
would be employed. Aside from the UPPER issue discussed above, a
second performance problem in this query is the use of suffix
search. In TimesTen (and most relational databases), indexes can
be used to optimize exact-match searches and prefix searches.
However, suffix searches must be performed by scanning every row in
the table ... an expensive and non-scalable proposition. Solution:
Back-sql was modified to optionally add a new "dn_ru" column to the
ldap_entries table. This additional column, if present, contains a
byte-reversed and upper cased version of the DN. This allows
back-sql to generate indexable prefix searches. This column is
also easily maintained automatically through the use of triggers.
Results
A simple database schema was generated holding the LDAP objects and
attributes specified by our customer. An application was written to
generate test databases. Both TimesTen and Oracle 8.1.7 were
populated with 100,000 entry databases.
Load Times
Using "slapadd" followed by "slapindex", loading and indexing 100,000
entries in an LDBM database ran for 19 minutes 10 seconds.
Using a C++ application that used ODBC, loading 100,000 entries into
a disk based RDBMS took 17 minutes 53 seconds.
Using a C++ application that used ODBC, loading 100,000 entries into
TimesTen took 1 minute 40 seconds.
Search Times
The command, "timex timesearch.sh '(cn=fname210100*)'" was used to
test search times. This command issues the same LDAP search 4000
times over a single LDAP connection. Both the client and server
(slapd) were run on the same machine.
With TimesTen as the database, 4000 queries took 14.93 seconds, for a
rate of 267.9 per second.
With a disk based RDBMS as the database, 4000 queries took 77.79 seconds,
for a
rate of 51.42 per second.
With LDBM as the database, 1 query takes 76 seconds, or 0.076 per
second. Something is clearly broken.
- filter -> SQL translation bugfixes
- several memory leaks fixups
- improved configurability:
- allows definition of uppercasing function to support CIS matching on databases that do
case sensitive compares (this fixes up Oracle issues, example updated)
- allows more flexibility in stored procedures interface (different parameter order, optional return
codes - see samples, and comments in backsql.h)
- synchronize function interfaces to recent changes in prototypes ("const" clauses etc.) made for all backends
(those changes led to compile-time errors)
