I have three microservices, communicating via Kafka. I am using Brave's #Tracer. The trace id is generated consistently however the parentId is different in microservices 2 and 3. What can we generate consistent parentId all over the microservices?
Thanks.
What version of Sleuth are you using? If it's 3.x, please use Sleuth's Tracer instead of Brave's.
Since Spans are representing operations, the spanId will be different for every Span, the parentId is really mean the Id of the previous (parent) Span so it is completely normal if the parentId is not the same for two different Spans (if they don't share the same parent).
Please see the docs: https://docs.spring.io/spring-cloud-sleuth/docs/current/reference/htmlsingle/#getting-started-terminology
The parentIds of the Spans here are the following:
Span A: null
Span B: A
Span C: B
Span D: C
Span E: D
Span F: C
Span G: F
Related
I am saving the best solution into the DB, and we display that on the web page. I am looking for some solution where a user can add more visits, but that should not change already published trips.
I have checked the documentation and found ProblemFactChange can be used, but only when the solver is already running.
In my case solver is already terminated and the solution is also published. Now I want to add more visits to the vehicle without modifying the existing visits of the Vehicle. Is this possible with Optaplanner? if yes any example of documentation would be very helpful.
You can use PlanningPin annotation for avoiding unwanted changes.
Optaplanner - Pinned planning entities
If you're not looking for pinning (see Ismail's excellent answer), take a look at the OptaPlanner School Timetabling example, which allows adding lessons between solver runs. The lessons simply get stored in the database and then get loaded when the solver starts.
The difficulty with VRP is the chained model complexity (we're working on an alternative): If you add a visit X between A and B, then make sure that afterwards A.next = X, B.previous = X, X.previous = A, X.next = B and X.vehicle = A.vehicle. Not the mention the arrival times etc.
My suggestion would be to resolve what is left after the changes have been introduced. Let's say you are you visited half of your destinations (A -> B -> C) but not yet (C - > D -> E) when two new possible destinations (D' and E') are introduced. Would not this be the same thing as you are starting in C and trying plan for D, D', E and E'? The solution needs to be updated on the progress though so the remainder + changes can be input to the next solution.
Just my two cent.
The project I am working on involves static offline GTFS data in a mobile app. All the GTFS data is available inside realm-objects (or SQLite if needed).
Now, I would like to establish all train- or bus-connections from A to B (starting after a certain departure-time).
How do I query the GTFS-data in order to get a connection from A to B ???
I reealized to get all trips leaving from A.
I realized to get all station-names along that trip including times.
But I find it very hard to get the connection information between two locations A and B. What SQL queries do i have to set up in order to get that information ?
Any help appreciated !
If you just want to dynamically calculate shortest travel routes between static hubs, in an offline application, determined like the following image, you can use the following formula:
(Source)
Here's the pseudo code:
1 function Dijkstra(Graph, source):
2
3 create vertex set Q
4
5 for each vertex v in Graph: // Initialization
6 dist[v] ← INFINITY // Unknown distance from source to v
7 prev[v] ← UNDEFINED // Previous node in optimal path from source
8 add v to Q // All nodes initially in Q (unvisited nodes)
9
10 dist[source] ← 0 // Distance from source to source
11
12 while Q is not empty:
13 u ← vertex in Q with min dist[u] // Node with the least distance
14 // will be selected first
15 remove u from Q
16
17 for each neighbor v of u: // where v is still in Q.
18 alt ← dist[u] + length(u, v)
19 if alt < dist[v]: // A shorter path to v has been found
20 dist[v] ← alt
21 prev[v] ← u
22
23 return dist[], prev[]
(Source)
Alright, I'll admit so far my answer was a tad facetious...
I suspect you don't realize just how complicated it is to do what you're asking, especially in an offline environment. Companies like Google and Microsoft have spent millions on research with huge teams of data scientists.
If this is something you are serious about, I'd encourage you to start with a 10×10 grid and work on the logic of getting from "Point A → Point B" when you start adding barriers in random places (this simulating roads beginning & ending). Recently I was surprised how complicated a seemingly-simple, somewhat-related Stack Overflow "pipe sizes conversion" question that I answered had become.
If you didn't have the "offline" condition, I would've suggested looking into getting a [free] API Key for Google Web Services Directions API. Basically you tell it a where Points A & B are, and it gives you detailed route information, via transit or other methods.
Another of Google's many API's that could be helpful is the Snap to Roads API, which turns partial or error-ridden paths into driveable ones.
The study Route Logic and Shortest Path Logic is actually really fascinating stuff, and there are some amazing resources to learn about the related theories (see below), including a video from Google explaining how they went about it.
...but unfortunately this isn't something that's going to be accomplished with a simple SQL Query.
Actual Resources:
YouTube : Google Tech Talk: Fast Route Planning
Wikipedia : Shortest path problem
Wikipedia : Dijkstra's algorithm
...and some slightly Lighter Reading:
Wikipedia : Travelling Salesman Problem
Why UPS drivers don’t turn left and you probably shouldn’t either
Google Web Services : Directions API Developer's Guide
Stack Overflow : Shortest Route of converters between two different pipe sizes?
Wikipedia : Seven Bridges of Königsberg
Am new to Neo4j and trying to do a POC by implementing a graph DB for Enterprise Reference / Integration Architecture (Architecture showing all enterprise applications as Nodes, Underlying Tables / APIs - logically grouped as Nodes, integrations between Apps as Relationships.
Objective is to achieve seamlessly 'Impact Analysis' using the strength of Graph DB (Note: I understand this may be an incorrect approach to achieve whatever am trying to achieve, so suggestions are welcome)
Let me come brief my question now,
There are four Apps - A1, A2, A3, A4; A1 has set of Tables (represented by a node A1TS1) that's updated by Integration 1 (relationship in this case) and the same set of tables are read by Integration 2. So the Data model looks like below
(A1TS1)<-[:INT1]-(A1)<-[:INT1]-(A2)
(A1TS1)-[:INT2]->(A1)-[:INT2]->(A4)
I have the underlying application table names captured as a List property in A1TS1 node.
Let's say one of the app table is altered for a new column or Data type and I wanted to understand all impacted Integrations and Applications. Now am trying to write a query as below to retrieve all nodes & relationships that are associated/impacted because of this table alteration but am not able to achieve this
Expected Result is - all impacted nodes (A1TS1, A1, A2, A4) and relationships (INT1, INT2)
Option 1 (Using APOC)
MATCH (a {TCName:'A1TS1',AppName:'A1'})-[r]-(b)
WITH a as STRTND, Collect(type(r)) as allr
CALL apoc.path.subgraphAll(STRTND, {relationshipFilter:allr}) YIELD nodes, relationships
RETURN nodes, relationships
This faile with error Failed to invoke procedure 'apoc.path.subgraphAll': Caused by: java.lang.ClassCastException: java.util.ArrayList cannot be cast to java.lang.String
Option 2 (Using with, unwind, collect clause)
MATCH (a {TCName:'A1TS1',AppName:'A1'})-[r]-(b)
WITH a as STRTND, Collect(r) as allr
UNWIND allr as rels
MATCH p=()-[rels]-()-[rels]-()
RETURN p
This fails with error "Cannot use the same relationship variable 'rels' for multiple patterns" but if I use the [rels] once like p=()-[rels]=() it works but not yielding me all nodes
Any help/suggestion/lead is appreciated. Thanks in advance
Update
Trying to give more context
Showing the Underlying Data
MATCH (TC:TBLCON) RETURN TC
"TC"
{"Tables":["TBL1","TBL2","TBL3"],"TCName":"A1TS1","AppName":"A1"}
{"Tables":["TBL4","TBL1"],"TCName":"A2TS1","AppName":"A2"}
MATCH (A:App) RETURN A
"A"
{"Sponsor":"XY","Platform":"Oracle","TechOwnr":"VV","Version":"12","Tags":["ERP","OracleEBS","FinanceSystem"],"AppName":"A1"}
{"Sponsor":"CC","Platform":"Teradata","TechOwnr":"RZ","Tags":["EDW","DataWarehouse"],"AppName":"A2"}
MATCH ()-[r]-() RETURN distinct r.relname
"r.relname"
"FINREP" │ (runs between A1 to other apps)
"UPFRNT" │ (runs between A2 to different Salesforce App)
"INVOICE" │ (runs between A1 to other apps)
With this, here is what am trying to achieve
Assume "TBL3" is getting altered in App A1, I wanted to write a query specifying the table "TBL3" in match pattern, get all associated relationships and connected nodes (upstream)
May be I need to achieve in 3 steps,
Step 1 - Write a match pattern to find the start node and associated relationship(s)
Step 2 - Store that relationship(s) from step 1 in a Array variable / parameter
Step 3 - Pass the start node from step 1 & parameter from step 2 to apoc.path.subgraphAll to see all the impacted nodes
This may conceptually sound valid but how to do that technically in neo4j Cypher query is the question.
Hope this helps
This query may do what you want:
MATCH (tc:TBLCON)
WHERE $table IN tc.Tables
MATCH p=(tc)-[:Foo*]-()
WITH tc,
REDUCE(s = [], x IN COLLECT(NODES(p)) | s + x) AS ns,
REDUCE(t = [], y IN COLLECT(RELATIONSHIPS(p)) | t + y) AS rs
UNWIND ns AS n
WITH tc, rs, COLLECT(DISTINCT n) AS nodes
UNWIND rs AS rel
RETURN tc, nodes, COLLECT(DISTINCT rel) AS rels;
It assumes that you provide the name of the table of interest (e.g., "TBL3") as the value of a table parameter. It also assumes that the relationships of interest all have the Foo type.
It first finds tc, the TBLCON node(s) containing that table name. It then uses a variable-length non-directional search for all paths (with non-repeating relationships) that include tc. It then uses COLLECT twice: to aggregate the list of nodes in each path, and to aggregate the list of relationships in each path. Each aggregation result would be a list of lists, so it uses REDUCE on each outer list to merge the inner lists. It then uses UNWIND and COLLECT(DISTINCT x) on each list to produce a list with unique elements.
[UPDATE]
If you differentiate between your relationships by type (rather than by property value), your Cypher code can be a lot simpler by taking advantage of APOC functions. The following query assumes that the desired relationship types are passed via a types parameter:
MATCH (tc:TBLCON)
WHERE $table IN tc.Tables
CALL apoc.path.subgraphAll(
tc, {relationshipFilter: apoc.text.join($types, '|')}) YIELD nodes, relationships
RETURN nodes, relationships;
WIth some lead from cybersam's response, the below query gets me what I want. Only constraint is, this result is limited to 3 layers (3rd layer through Optional Match)
MATCH (TC:TBLCON) WHERE 'TBL3' IN TC.Tables
CALL apoc.path.subgraphAll(TC, {maxLevel:1}) YIELD nodes AS invN, relationships AS invR
WITH TC, REDUCE (tmpL=[], tmpr IN invR | tmpL+type(tmpr)) AS impR
MATCH FLP=(TC)-[]-()-[FLR]-(SL) WHERE type(FLR) IN impR
WITH FLP, TC, SL,impR
OPTIONAL MATCH SLP=(SL)-[SLR]-() WHERE type(SLR) IN impR RETURN FLP,SLP
This works for my needs, hope this might also help someone.
Thanks everyone for the responses and suggestions
****Update****
Enhanced the query to get rid of Optional Match criteria and other given limitations
MATCH (initTC:TBLCON) WHERE $TL IN initTC.Tables
WITH Reduce(O="",OO in Reduce (I=[], II in collect(apoc.node.relationship.types(initTC)) | I+II) | O+OO+"|") as RF
MATCH (TC:TBLCON) WHERE $TL IN TC.Tables
CALL apoc.path.subgraphAll(TC,{relationshipFilter:RF}) YIELD nodes, relationships
RETURN nodes, relationships
Thanks all (especially cybersam)
Is it possible to handle relations between jobs (in this case services) in jsprit?
For instance one job has to start at the same time with one or more other jobs.
Or one job must not start before the end of another job (normal sequence).
If not, do you know other java libraries that can handle such kind of restrictions?
Thank you!
Yes you can handle such relations with jsprit.
It is a bit of coding, but - I think - easy to implement. To illustrate it, I prepared you five examples that are based on the Vehicle Routing Problems (VRP) developed by Christofides-Mingozzi-Toth's* (first benchmarking instance). Follow the links behind the individual headlines and you get to the code. Note that the first activity in a route is marked with a triangle. The labels denote jobIds.
noConstraints
capacityConstraints
job 13 and 21 in same route
job 13 and 21 in same route AND 21 before 13
job 13 and 21 in same route AND 13 right after 21
Visit http://jsprit.github.io/ and you get to a number of code examples and docs.
*N. Christofides, A. Mingozzi, and P. Toth. The vehicle routing problem. In N. Christofides, A. Mingozzi, P. Toth, and C. Sandi, editors, Combinatorial Optimization. John Wiley, Chichester, 1979.
I have a relation called conversations_grouped made up of bags of tuples of varying sizes, like so:
DUMP conversations_grouped:
...
({(L194),(L195),(L196),(L197)})
({(L198),(L199)})
({(L200),(L201),(L202),(L203)})
({(L204),(L205),(L206)})
({(L207),(L208)})
({(L271),(L272),(L273),(L274),(L275)})
({(L276),(L277)})
({(L280),(L281)})
({(L363),(L364)})
({(L365),(L366)})
({(L666256),(L666257)})
({(L666369),(L666370),(L666371),(L666372)})
({(L666520),(L666521),(L666522)})
Each L[0-9]+ is a tag corresponding to a string. For example, L194 might be "Hello, how are you doing?" and L195 might be "fine, how are you?". This correspondence is maintained by a map called line_map. Here's a sample:
DUMP line_map;
...
([L666324#Do you think she might be interested in someone?])
([L666264#Well that's typical of Her Majesty's army. Appoint an engineer to do a soldier's work.])
([L666263#Um. There are rumours that my Lord Chelmsford intends to make Durnford Second in Command.])
([L666262#Lighting COGHILL' 5 cigar: Our good Colonel Dumford scored quite a coup with the Sikali Horse.])
([L666522#So far only their scouts. But we have had reports of a small Impi farther north, over there. ])
([L666521#And I assure you, you do not In fact I'd be obliged for your best advice. What have your scouts seen?])
([L666520#Well I assure you, Sir, I have no desire to create difficulties. 45])
([L666372#I think Chelmsford wants a good man on the border Why he fears a flanking attack and requires a steady Commander in reserve.])
([L666371#Lord Chelmsford seems to want me to stay back with my Basutos.])
([L666370#I'm to take the Sikali with the main column to the river])
([L666369#Your orders, Mr Vereker?])
([L666257#Good ones, yes, Mr Vereker. Gentlemen who can ride and shoot])
([L666256#Colonel Durnford... William Vereker. I hear you 've been seeking Officers?])
What I'm trying to do now is parse through each line and replace the L[0-9]+ tags with their corresponding text from line_map. Is it possible to make references to line_map from within a Pig FOREACH statement, or is there something else I have to do?
The first issue with this is that in a map the key must be a quoted string. So you can't use a schema value to access the map. E.G. This will not work.
C: {foo: chararray, M: [value:chararray]}
D = FOREACH C GENERATE M#foo ;
The solution that comes to mind is to FLATTEN conversations_grouped. Then do a join between conversations_grouped and line_map on the L[0-9]+ tag. You'll probably want to project out some of the extra fields (like the L[0-9]+ tag after the join) to make the next step faster. After that you'll have to regroup the data, and massage it into the correct format.
This won't work unless each bag has it's own unique ID for the regrouping, but if each of the L[0-9]+ tags appear in only one bag (conversation) you can use this to create a unique id.
-- A is dumped conversations_grouped
B = FOREACH A {
-- Pulls out an element from the bag to use as the id
id = LIMIT tags 1 ;
-- Flattens B into id, tag form. Each group of tags will have the same id.
GENERATE FLATTEN(id), FLATTEN(tags) ;
}
The schema and output for B is:
B: {id: chararray,tags::tag: chararray}
(L194,L194)
(L194,L195)
(L194,L196)
(L194,L197)
(L198,L198)
(L198,L199)
(L200,L200)
(L200,L201)
(L200,L202)
(L200,L203)
(L204,L204)
(L204,L205)
(L204,L206)
(L207,L207)
(L207,L208)
(L271,L271)
(L271,L272)
(L271,L273)
(L271,L274)
(L271,L275)
(L276,L276)
(L276,L277)
(L280,L280)
(L280,L281)
(L363,L363)
(L363,L364)
(L365,L365)
(L365,L366)
(L666256,L666256)
(L666256,L666257)
(L666369,L666369)
(L666369,L666370)
(L666369,L666371)
(L666369,L666372)
(L666520,L666520)
(L666520,L666521)
(L666520,L666522)
Assuming that the tags are unique, the rest is done like:
-- A2 is line_map, loaded in tag/message pairs instead of a map
-- Joins conversations_grouped and line_map on tag
C = FOREACH (JOIN B by tags::tag, A2 by tag)
-- This generate removes the tag
GENERATE id, message ;
-- Regroups C on the id created in B
D = FOREACH (GROUP C BY id)
-- This step limits the output to just messages
GENERATE C.(message) AS messages ;
Schema and output from D:
D: {messages: {(A2::message: chararray)}}
({(Colonel Durnford... William Vereker. I hear you 've been seeking Officers?),(Good ones, yes, Mr Vereker. Gentlemen who can ride and shoot)})
({(Your orders, Mr Vereker?),(I'm to take the Sikali with the main column to the river),(Lord Chelmsford seems to want me to stay back with my Basutos.),(I think Chelmsford wants a good man on the border Why he fears a flanking attack and requires a steady Commander in reserve.)})
({(Well I assure you, Sir, I have no desire to create difficulties. 45),(And I assure you, you do not In fact I'd be obliged for your best advice. What have your scouts seen?),(So far only their scouts. But we have had reports of a small Impi farther north, over there. )})
NOTE: If at worst, (the L[0-9]+ tags aren't unique) you can give each line of the input file(s) a sequential, integer id before you load it into pig.
UPDATE: If you are using pig 0.11, then you can also use the RANK operator.