Background

The current implementation of Cps Path queries relies on regular expressions in the generated SQL queries.

For example, given this Cps Path:

/bookstore/categories[@code="1"]/books[@title="Matilda"]

the following SQL query is generated:

SELECT
    * 
FROM
    FRAGMENT 
WHERE
    anchor_id = 3
    AND xpath ~ '/bookstore/categories\[@code=''1'']/books(\[@(?!.*\[).*?])?$' 
    AND (
        attributes @> '{"title":"Matilda"}'
    )

The use of regex potentially results in full table scans, severely limiting performance, and causing query time duration to grow linearly with the fragment table size (i.e. queries get slower as the DB gets bigger).

A new algorithm for queries is being proposed, avoiding regex, so that query duration is independent of database size.

Objective

To achieve the maximum theoretical performance for queries.

• For a query that will return 1 out of N items, the best theoretical time complexity is constant, O(1).
• For a query that will return all N items, the best theoretical time complexity is linear, O(N).

Complexity of existing solution

As will be demonstrated by performance tests later in this document, the existing solution has the following performance characteristics:

• For a query that will return 1 out of N items, the current time complexity is linear, O(N).
• For a query that will return all N items, the current time complexity is quadratic, O(N²).

Proposal

The new approach involves adding a column to the Fragment table, storing the last path component (called xpath_component here). The new column is indexed, to allow constant-time lookups.

The new approach will first look for "bookstore", and using that as the parent ID, look for ''categories[@code='1']", and using that as parent ID, look for "books" or xpath component starting with "books[", before finally applying leaf condition checks.

For example, given this Cps Path:

/bookstore/categories[@code="1"]/books[@title="Matilda"]

the following SQL query is generated:

SELECT
    * 
FROM
    fragment 
WHERE
    parent_id IN (
        SELECT
            id 
        FROM
            fragment 
        WHERE
            xpath_component = 'categories[@code=''1'']'
            AND parent_id = (
                SELECT
                    id 
                FROM
                    fragment 
                WHERE
                    xpath_component = 'bookstore'
                    AND anchor_id = 3
                    AND parent_id IS NULL
            )
        ) 
        AND (
            xpath_component = 'books'
            OR xpath_component LIKE 'books[%'
        ) 
        AND (
            attributes @> '{"title":"Matilda"}'
        )

A note on fetching descendant nodes

The above sections only partly describe the current and proposed solutions. In both cases, a CPS path query is actually send as two database queries:

• the first query performs the CPS path query
• the second query fetches the descendants, if required
  • alternatively, if an ancestor CPS path was provided, the second query would fetch the ancestors (with descendants if required)

The current implementation uses a regex-based query to fetch descendants, while the proposed solution will use recursive SQL to fetch descendants of fragment returned from the CPS path query:

WITH RECURSIVE descendant_search AS (
  SELECT id, 0 AS depth
    FROM fragment
   WHERE id IN (:fragmentIds)
   UNION
  SELECT child.id, depth + 1
    FROM fragment child INNER JOIN descendant_search ds ON child.parent_id = ds.id
   WHERE depth <= :maxDepth
) 
SELECT f.id, anchor_id AS anchorId, xpath, f.parent_id AS parentId, CAST(attributes AS TEXT) AS attributes 
FROM fragment f INNER JOIN descendant_search ds ON f.id = ds.id

Proof of Concept

A PoC was developed so that performance could be compared against existing Cps Path Query algorithms.

Test data

These tests were performed using the openroadm model, present in the integration-test module of CPS source code repo.

In this case, each 'device' node is comprised of 86 cps data nodes. In these tests, 4 anchors were populated using the same data.

Performance Improvement

Query one device from many, using descendant cps path

In this case, a query that matches a single device node is executed, such as:

//openroadm-device[@device-id="C201-7-1A-14"]

As seen in the graphs, query performance for current master branch is linear on the size of the database, while the PoC implementation is constant time (independent of DB size).

(Note, I have not illustrated all different fetchDescendantOptions, as it has only minor impact in this case of fetching 1 device node.

Query all devices using descendant cps path

In this case, a query that matches many device nodes using a descendant cps path is executed:

//openroadm-device[@ne-state="inservice"]

In above cases, it is observed that the existing algorithm grows quadratically - O(n²), e.g. doubling from 1000 to 2000 nodes takes 4 times longer (going from 40 to 160 seconds).

The PoC algorithm grows linearly - O(n), e.g. doubling from 1000 to 2000 nodes takes 2 times longer (going from 3.5 to 7 seconds).

Query all devices using absolute cps path

In this case, a query that matches many device nodes using an absolute cps path is executed:

/openroadm-devices/openroadm-device[@status="success"]

In above cases, it is observed that the existing algorithm grows quadratically - O(n²), while the PoC algorithm grows linearly - O(n).

Summary of performance

As can be seen in the cases below, the existing algorithm using regex has linear time complexity based on the the size of the fragment table. The new algorithm is constant time.

• For querying 1 out of many nodes, existing algorithm is linear time (linear on fragment table size).
• For querying 1 out of many nodes, new algorithm is constant time.
• For querying all nodes, existing algorithm is quadratic on fragment table size.
• For querying all nodes, new algorithm is linear on fragment table size.
• In all cases, there is an easily observed massive reduction in query duration using new algorithm.

Work Breakdown

In addition to the changes outlined above, there is additional work remaining for this change to be production-ready. 

The main algorithm was mostly done during the PoC (all integration tests are passing for the PoC). The existing PoC code can thus be refactored to make it production ready.

DB upgrade

Because a new column is being added to the Fragment table, this column needs to be populated. An SQL script will be needed to provide a value for of the new xpath_component field based on existing xpath field.

Cps Path Parser changes

CpsPathBuilder and CpsPathQuery classes from cps-path-parser module will need to be updated to provide the individual path components.