Performance problems with XMLTABLE and XMLQUERY involving relational data

Question

Hello-
Is anyone out there using XMLTABLE or XMLQUERY with more than a toy set of data? I am running into serious performance problems tyring to do basic things such as:
* Combine records in 10 relational tables into a single table of XMLTYPE records using XMLTABLE. This hangs indefinitely for any more than 800 records. Oracle has confirmed that this is a problem and is working on a fix.
* Combine a single XMLTYPE record with several relational code tables into a single XMLTYPE record using XMLQUERY and ora:view() to insert code descriptions after each code. Performance is 10 seconds for 10 records (terrible) passing a batch of records , or 160 seconds for one record (unacceptable!). How can it take 10 times longer to process 1/10th the number of records? Ironically, the query plan says it will do a full table scan of records for the batch, but an index access for the one record passed to the XMLQUERY.
I am rapidly losing faith in XML DB, and desparately need some hints on how to work around these performance problems, or at least some assurance that others have been able to get this thing to perform.

Answer 1

<Note>Long post, sorry.</Note>
First, thanks for the responses above. I'm impressed with the quality of thought put into them. (Do the forum rules allow me to offer rewards? :) One suggestion in particular made a big performance improvement, and I’m encouraged to hear of good performance in pure XML situations. Unfortunately, I think there is a real performance challenge in two use cases that are pertinent to the XML+relational subject of this post and probably increasingly common as XML DB usage increases:
•     Converting legacy tabular data into XML records; and
•     Performing code table lookups for coded values in XML records.
There are three things I want to accomplish with this post:
•     Clarify what we are trying to accomplish, which might expose completely different approaches than I have tried
•     Let you know what I tried so far and the rationale for my approach to help expose flaws in my thinking and share what I have learned
•     Highlight remaining performance issues in hopes that we can solve them
What we are trying to accomplish:
•     Receive a monthly feed of 10,000 XML records (batched together in text files), each containing information about an employee, including elements that repeat for every year of service. We may need to process an annual feed of 1,000,000 XML records in the future.
•     Receive a one-time feed of 500,000 employee records stored in about 10 relational tables, with a maximum join depth of 2 or 3. This is inherently a relational-to-XML process. One record/second is minimally acceptable, but 10 records/sec would be better.
•     Consolidate a few records (from different providers) for each employee into a single record. Given the data volume, we need to achieve a minimum rate of 10 records per second. This may be an XML-only process, or XML+relational if code lookups are done during consolidation.
•     Allow the records to be viewed and edited, with codes resolved into user-friendly descriptions. Since a user is sitting there, code lookups done when a record is viewed (vs. during consolidation) should not take more than 3 seconds total. We have about 20 code tables averaging a few hundred rows each, though one has 450,000 rows.
As requested earlier, I have included code at the end of this post for example tables and queries that accurately (but simply) replicate our real system.
Why we did and why:
•     Stored the source XML records as CLOBS: We did this to preserve the records exactly as they were certified and sent from providers. In addition, we always access the entire XML record as a whole (e.g., when viewing a record or consolidating employee records), so this storage model seemed like a good fit. We can copy them into another format if necessary.
•     Stored the consolidated XML employee records as “binary XML”. We did this because we almost always access a single, entire record as a whole (for view/edit), but might want to create some summary statistics at some point. Binary XML seemed the best fit.
•     Used ora:view() for both tabular source records and lookup tables. We are not aware of any alternatives at this time. If it made sense, most code tables could be pre-converted into XML documents, but this seemed risky from a performance standpoint because the lookups use both code and date range constraints (the meaning of codes changes over time).
•     Stored records as XMLTYPE columns in a table with other key columns on the table, plus an XMLTYPE metadata column. We thought this would facilitate pulling a single record (or a few records for a given employee) quickly. We knew this might be unnecessary given XML indexes and virtual columns, but were not experienced with those and wanted the comfort of traditional keys. We did not used XMLTYPE tables or the XML Repository for documents.
•     Used XMLTABLE to consolidate XML records by looping over each distinct employee ID in the source batch. We also tried XMLQUERY and it seems to perform about the same. We can achieve 10 to 20 records/second if we do not do any code lookups during consolidation, just meeting our performance requirement, but still much slower than expected.
•     Used PL/SQL with XMLFOREST to convert tabular source records to XML by looping over distinct employee IDs. We tried this outside PL/SQL both with XMLFOREST and XMLTABLE+ora:view(), but it hangs in both cases for more than 800 records (a known/open issue). We were able to get it to work by using an explicit cursor to loop over distinct employee IDs (rather than processing all records at once within the query). The performance is one record/second, which is minimally acceptable and interferes with other database activity.
•     Used XMLQUERY plus ora:view() plus XPATH constraints to perform code lookups. When passing a single employee record, the response time ranges from 1 sec to 160 sec depending on the length of the record (i.e., number of years of service). We achieved a 5-fold speedup using an XMLINDEX (thank you Marco!!). The result may be minimally acceptable, but I’m baffled why the index would be needed when processing a single XML record. Other things we tried: joining code tables in the FOR...WHERE clauses, joining code tables using LET with XPATH constraints and LET with WHERE clause constraints, and looking up codes individually via JDBC from the application code at presentation time. All those approaches were slower. Note: the difference I mentioned above in equality/inequality constraint performance was due to data record variations not query plan variations.
What issues remain?
We have a minimally acceptable solution from a performance standpoint with one very awkward PL/SQL workaround. The performance of a mixed XML+relational data query is still marginal IMHO, until we properly utilize available optimizations, fix known problems, and perhaps get some new query optimizations. On the last point, I think the query plan for tabular lookups of codes in XML records is falling short right now. I’m reminded of data warehousing in the days before hash joins and star join optimization. I would be happy to be wrong, and just as happy for viable workarounds if I am right!
Here are the details on our code lookup challenge. Additional suggestions would be greatly appreciated. I’ll try to post more detail on the legacy table conversion challenge later.
-- The main record table:
create table RECORDS (
SSN varchar2(20),
XMLREC sys.xmltype
xmltype column XMLREC store as binary xml;
create index records_ssn on records(ssn);
-- A dozen code tables represented by one like this:
create table CODES (
CODE varchar2(4),
DESCRIPTION varchar2(500)
create index codes_code on codes(code);
-- Some XML records with coded values (the real records are much more complex of course):
-- I think this took about a minute or two
DECLARE
ssn varchar2(20);
xmlrec xmltype;
i integer;
BEGIN
xmlrec := xmltype('<?xml version="1.0"?>
<Root>
<Id>123456789</Id>
<Element>
<Subelement1><Code>11</Code></Subelement1>
<Subelement2><Code>21</Code></Subelement2>
<Subelement3><Code>31</Code></Subelement3>
</Element>
<Element>
<Subelement1><Code>11</Code></Subelement1>
<Subelement2><Code>21</Code></Subelement2>
<Subelement3><Code>31</Code></Subelement3>
</Element>
<Element>
<Subelement1><Code>11</Code></Subelement1>
<Subelement2><Code>21</Code></Subelement2>
<Subelement3><Code>31</Code></Subelement3>
</Element>
</Root>
for i IN 1..100000 loop
insert into records(ssn, xmlrec) values (i, xmlrec);
end loop;
commit;
END;
-- Some code data like this (ignoring date ranges on codes):
DECLARE
description varchar2(100);
i integer;
BEGIN
description := 'This is the code description ';
for i IN 1..3000 loop
insert into codes(code, description) values (to_char(i), description);
end loop;
commit;
end;
-- Retrieve one record while performing code lookups. Takes about 5-6 seconds...pretty slow.
-- Each additional lookup (times 3 repeating elements in the data) adds about 1 second.
-- A typical real record has 5 Elements and 20 Subelements, meaning more than 20 seconds to display the record
-- Note we are accessing a single XML record based on SSN
-- Note also we are reusing the one test code table multiple times for convenience of this test
select xmlquery('
for $r in Root
return
<Root>
<Id>123456789</Id>
{for $e in $r/Element
    return
    <Element>
      <Subelement1>
        {$e/Subelement1/Code}
<Description>
{ora:view("disaac","codes")/ROW[CODE=$e/Subelement1/Code]/DESCRIPTION/text() }
</Description>
</Subelement1>
<Subelement2>
{$e/Subelement2/Code}
<Description>
{ora:view("disaac","codes")/ROW[CODE=$e/Subelement2/Code]/DESCRIPTION/text()}
</Description>
</Subelement2>
<Subelement3>
{$e/Subelement3/Code}
<Description>
{ora:view("disaac","codes")/ROW[CODE=$e/Subelement3/Code]/DESCRIPTION/text() }
</Description>
</Subelement3>
</Element>
</Root>
' passing xmlrec returning content)
from records
where ssn = '10000';
The plan shows the nested loop access that slows things down.
By contrast, a functionally-similar SQL query on relational data will use a hash join and perform 10x to 100x faster, even for a single record. There seems to be no way for the optimizer to see the regularity in the XML structure and perform a corresponding optimization in joining the code tables. Not sure if registering a schema would help. Using structured storage probably would. But should that be necessary given we’re working with a single record?
Operation Object
|SELECT STATEMENT ()
| SORT (AGGREGATE)
| NESTED LOOPS (SEMI)
| TABLE ACCESS (FULL) CODES
| XPATH EVALUATION ()
| SORT (AGGREGATE)
| NESTED LOOPS (SEMI)
| TABLE ACCESS (FULL) CODES
| XPATH EVALUATION ()
| SORT (AGGREGATE)
| NESTED LOOPS (SEMI)
| TABLE ACCESS (FULL) CODES
| XPATH EVALUATION ()
| SORT (AGGREGATE)
| XPATH EVALUATION ()
| SORT (AGGREGATE)
| XPATH EVALUATION ()
| TABLE ACCESS (BY INDEX ROWID) RECORDS
| INDEX (RANGE SCAN) RECORDS_SSN
With an xmlindex, the same query above runs in about 1 second, so is about 5x faster (0.2 sec/lookup), which is almost good enough. Is this the answer? Or is there a better way? I’m not sure why the optimizer wants to scan the code tables and index into the (one) XML record, rather than the other way around, but maybe that makes sense if the optimizer wants to use the same general plan as when the WHERE clause constraint is relaxed to multiple records.
-- Add an xmlindex. Takes about 2.5 minutes
create index records_record_xml ON records(xmlrec)
indextype IS xdb.xmlindex;
Operation Object
|SELECT STATEMENT ()
| SORT (GROUP BY)
| FILTER ()
| NESTED LOOPS ()
| FAST DUAL ()
| TABLE ACCESS (BY INDEX ROWID) SYS113473_RECORDS_R_PATH_TABLE
| INDEX (RANGE SCAN) SYS113473_RECORDS_R_PATHID_IX
| SORT (AGGREGATE)
| FILTER ()
| TABLE ACCESS (FULL) CODES
| FILTER ()
| NESTED LOOPS ()
| FAST DUAL ()
| TABLE ACCESS (BY INDEX ROWID) SYS113473_RECORDS_R_PATH_TABLE
| INDEX (RANGE SCAN) SYS113473_RECORDS_R_PATHID_IX
| SORT (GROUP BY)
| FILTER ()
| NESTED LOOPS ()
| FAST DUAL ()
| TABLE ACCESS (BY INDEX ROWID) SYS113473_RECORDS_R_PATH_TABLE
| INDEX (RANGE SCAN) SYS113473_RECORDS_R_PATHID_IX
| SORT (AGGREGATE)
| FILTER ()
| TABLE ACCESS (FULL) CODES
| FILTER ()
| NESTED LOOPS ()
| FAST DUAL ()
| TABLE ACCESS (BY INDEX ROWID) SYS113473_RECORDS_R_PATH_TABLE
| INDEX (RANGE SCAN) SYS113473_RECORDS_R_PATHID_IX
| SORT (GROUP BY)
| FILTER ()
| NESTED LOOPS ()
| FAST DUAL ()
| TABLE ACCESS (BY INDEX ROWID) SYS113473_RECORDS_R_PATH_TABLE
| INDEX (RANGE SCAN) SYS113473_RECORDS_R_PATHID_IX
| SORT (AGGREGATE)
| FILTER ()
| TABLE ACCESS (FULL) CODES
| FILTER ()
| NESTED LOOPS ()
| FAST DUAL ()
| TABLE ACCESS (BY INDEX ROWID) SYS113473_RECORDS_R_PATH_TABLE
| INDEX (RANGE SCAN) SYS113473_RECORDS_R_PATHID_IX
| SORT (AGGREGATE)
| FILTER ()
| NESTED LOOPS ()
| FAST DUAL ()
| TABLE ACCESS (BY INDEX ROWID) SYS113473_RECORDS_R_PATH_TABLE
| INDEX (RANGE SCAN) SYS113473_RECORDS_R_PATHID_IX
| SORT (AGGREGATE)
| TABLE ACCESS (BY INDEX ROWID) SYS113473_RECORDS_R_PATH_TABLE
| INDEX (RANGE SCAN) SYS113473_RECORDS_R_PATHID_IX
| TABLE ACCESS (BY INDEX ROWID) RECORDS
| INDEX (RANGE SCAN) RECORDS_SSN
Am I on the right path, or am I totally using the wrong approach? I thought about using XSLT but was unsure how to reference the code tables.
I’ve done the best I can constraining the main record to a single row passed to the XMLQUERY. Given Mark’s post (thanks!) should I be joining and constraining the code tables in the SQL WHERE clause too? That’s going to make the query much more complicated, but right now we’re more concerned about performance than complexity.