Charm workflow is to manual. Isn't there a better way?

The charm workflow is very manual. After a person finishes his task, he must assign the current processor to the next person in the process flow. It would be nice if this was automated. In many cases (e.g. after development, after testing) It must go back to the change manager. It should not be necessary for this to be done manually. We are on sp17. Is there any way to make the workflow more automated?

Hi Avrohom,
I understand your idea "the processor is the one who is currently in charge"
and I discussed this topic with some SOLMAN consultants that shares also this idea but when I read the SAP documentation I am not convinced about this.
Your idea is possible to implement and I can explain you how to do this but my feeling is that this is not the right way to proceed.
The processor is the one who is responsible for the delivery of the correction and will organize the communication around it. (depending on the case it might be the developer, an analyst, the change manager or someone else)
There are different functions set-up by sap to cover the different roles (normally on person doesn't play many different functions at the same time).
If you are a player, in CHARM you only have to look the column corresponding to your role and depending on the status you know what you need to do.
On the way reverse depending on the status of a correction the processor or maybe the requester knows who to chase.
We are running with this concept since 9 months without trouble.
best regards Xavier

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Hi,
Summary:
Can anyone offer advice on how best to use JDO to perform
projection/aggregate queries? Is there a better way of doing what is
described below?
Details:
The web application I'm developing includes a GUI for ad-hoc reports on
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Each asset has one associated t.description and zero or one associated
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and here it is in SQL:
select t.description type, d.description description, count(*) count,
sum(a.purch_price) sumPurchPrice
from assets a
left outer join asset_descriptions d
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where a.atype_no = t.atype_no
group by t.description, d.description
order by t.description, d.description
it takes <100ms to produce 5300 rows from 83000 assets.
The nearest I have managed with JDO is (pseodo code):
perform projection query to get t.description, d.description for every asset
loop on results
if this is first time we've had this combination of t.description,
d.description
perform aggregate query to get aggregates for this combination
The java code is below. It takes about 16000ms (with debug/trace logging
off, c.f. 100ms for SQL).
If the inner query is commented out it takes about 1600ms (so the inner
query is responsible for 9/10ths of the elapsed time).
Timings exclude startup overheads like PersistenceManagerFactory creation
and checking the meta data against the database (by looping 5 times and
averaging only the last 4) but include PersistenceManager creation (which
happens inside the loop).
It would be too big a job for us to directly generate SQL from our generic
ad-hoc report GUI, so that is not really an option.
KodoQuery q1 = (KodoQuery) pm.newQuery(Asset.class);
q1.setResult(
"assetType.description, assetDescription.description");
q1.setOrdering(
"assetType.description ascending,
assetDescription.description ascending");
KodoQuery q2 = (KodoQuery) pm.newQuery(Asset.class);
q2.setResult("count(purchPrice), sum(purchPrice)");
q2.declareParameters(
"String myAssetType, String myAssetDescription");
q2.setFilter(
"assetType.description == myAssetType &&
assetDescription.description == myAssetDescription");
q2.compile();
Collection results = (Collection) q1.execute();
Set distinct = new HashSet();
for (Iterator i = results.iterator(); i.hasNext();) {
Object[] cols = (Object[]) i.next();
String assetType = (String) cols[0];
String assetDescription = (String) cols[1];
String type_description =
assetDescription != null
? assetType + "~" + assetDescription
: assetType;
if (distinct.add(type_description)) {
Object[] cols2 =
(Object[]) q2.execute(assetType,
assetDescription);
// System.out.println(
// "type "
// + assetType
// + ", description "
// + assetDescription
// + ", count "
// + cols2[0]
// + ", sum "
// + cols2[1]);
q2.closeAll();
q1.closeAll();

Neil,
It sounds like the problem that you're running into is that Kodo doesn't
yet support the JDO2 grouping constructs, so you're doing your own
grouping in the Java code. Is that accurate?
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-Patrick
Neil Bacon wrote:
Hi,
Summary:
Can anyone offer advice on how best to use JDO to perform
projection/aggregate queries? Is there a better way of doing what is
described below?
Details:
The web application I'm developing includes a GUI for ad-hoc reports on
JDO's. Unlike 3rd party tools that go straight to the database we can
implement business rules that restrict access to objects (by adding extra
predicates) and provide extra calculated fields (by adding extra get methods
to our JDO's - no expression language yet). We're pleased with the results
so far.
Now I want to make it produce reports with aggregates and projections
without instantiating JDO instances. Here is an example of the sort of thing
I want it to be capable of doing:
Each asset has one associated t.description and zero or one associated
d.description.
For every distinct combination of t.description and d.description (skip
those for which there are no assets)
calculate some aggregates over all the assets with these values.
and here it is in SQL:
select t.description type, d.description description, count(*) count,
sum(a.purch_price) sumPurchPrice
from assets a
left outer join asset_descriptions d
on a.adesc_no = d.adesc_no,
asset_types t
where a.atype_no = t.atype_no
group by t.description, d.description
order by t.description, d.description
it takes <100ms to produce 5300 rows from 83000 assets.
The nearest I have managed with JDO is (pseodo code):
perform projection query to get t.description, d.description for every asset
loop on results
if this is first time we've had this combination of t.description,
d.description
perform aggregate query to get aggregates for this combination
The java code is below. It takes about 16000ms (with debug/trace logging
off, c.f. 100ms for SQL).
If the inner query is commented out it takes about 1600ms (so the inner
query is responsible for 9/10ths of the elapsed time).
Timings exclude startup overheads like PersistenceManagerFactory creation
and checking the meta data against the database (by looping 5 times and
averaging only the last 4) but include PersistenceManager creation (which
happens inside the loop).
It would be too big a job for us to directly generate SQL from our generic
ad-hoc report GUI, so that is not really an option.
KodoQuery q1 = (KodoQuery) pm.newQuery(Asset.class);
q1.setResult(
"assetType.description, assetDescription.description");
q1.setOrdering(
"assetType.description ascending,
assetDescription.description ascending");
KodoQuery q2 = (KodoQuery) pm.newQuery(Asset.class);
q2.setResult("count(purchPrice), sum(purchPrice)");
q2.declareParameters(
"String myAssetType, String myAssetDescription");
q2.setFilter(
"assetType.description == myAssetType &&
assetDescription.description == myAssetDescription");
q2.compile();
Collection results = (Collection) q1.execute();
Set distinct = new HashSet();
for (Iterator i = results.iterator(); i.hasNext();) {
Object[] cols = (Object[]) i.next();
String assetType = (String) cols[0];
String assetDescription = (String) cols[1];
String type_description =
assetDescription != null
? assetType + "~" + assetDescription
: assetType;
if (distinct.add(type_description)) {
Object[] cols2 =
(Object[]) q2.execute(assetType,
assetDescription);
// System.out.println(
// "type "
// + assetType
// + ", description "
// + assetDescription
// + ", count "
// + cols2[0]
// + ", sum "
// + cols2[1]);
q2.closeAll();
q1.closeAll();

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