Yes, I agree --id-type ACTUAL will guarantee this constraint.

On Monday, June 15, 2015 at 9:43:38 PM UTC+2, Zongheng Yang wrote:
>
> Fantastic, in my case the ids are exactly the sequence [0, 1, ..., N] 
> without gaps, unique, and in that order.
>
> Thanks both of you for the help!
>
> On Monday, June 15, 2015 at 12:34:18 PM UTC-7, Michael Hunger wrote:
>>
>> No, --id-type actual 
>> would but then you have to make sure to have globally unique incrementing 
>> id's without large holes in the distribution.
>>
>>
>> Am 15.06.2015 um 21:31 schrieb Zongheng Yang <zongh...@gmail.com>:
>>
>> I see.  Would setting the `--processors 1` flag for neo4j-import make 
>> internal ids and external ids match in my case?  (I understand this is an 
>> implementation detail and not a user-facing property.)
>>
>> On Monday, June 15, 2015 at 12:07:56 PM UTC-7, Michael Hunger wrote:
>>>
>>> GraphDatabaseService#getNodeById(long id)
>>>
>>>
>>> takes Neo4j internal ids.
>>>
>>> Michael
>>>
>>> Am 15.06.2015 um 20:59 schrieb Zongheng Yang <zongh...@gmail.com>:
>>>
>>> Hi Mattias,
>>>
>>> Thanks for looking into this.  I understand the difference between Neo4j 
>>> internal ids vs. the ids supplied in the csv. 
>>>
>>> However for say GraphDatabaseService#getNodeById(long id), does this 
>>> function take the user-supplied ids or Neo4j's internal ids?
>>>
>>> If it is the former: then the conceptual mismatch doesn't fully explain 
>>> the problem (e.g. I queried the nodes/edges using user-supplied ids, and 
>>> the internal ids should not mess up with the query results).  If it is the 
>>> latter, then for users programming using the Java Core API, how should they 
>>> get these correct internal ids (they only know application-supplied ids).
>>>
>>> Best,
>>> Zongheng
>>>
>>> On Monday, June 15, 2015 at 5:23:24 AM UTC-7, Mattias Persson wrote:
>>>>
>>>> Hello again, I'm quite confident I know what's happening here. The 
>>>> problem is the misconception that your INTEGER ids defined in the csv 
>>>> files 
>>>> will map 1-to-1 to the neo4j node/relationship ids in the store. They will 
>>>> actually match in most cases, but that's merely a coincidence.
>>>>
>>>> What you're seeing is the result of some parallelism happening in the 
>>>> importer where batches of 10k nodes/relationships flows through different 
>>>> steps, where some steps may execute multiple batches in parallel and 
>>>> doesn't care if reordering happens. Ids are assigned at the end.
>>>>
>>>> You're looking at the ids and see that they mismatch, but if you look 
>>>> at their data you should see that all relationships match the csv files. 
>>>> So 
>>>> please disregard the seemingly close match of neo4j node/relationship ids 
>>>> with the csv input ids as they are quite different in nature.
>>>>
>>>> On Thursday, June 11, 2015 at 11:32:55 AM UTC+2, Mattias Persson wrote:
>>>>>
>>>>> Hi, I'm one of the main authors of the import tool and I find this 
>>>>> issue quite interesting.
>>>>>
>>>>> Would you be able to share your dataset with me personally, for the 
>>>>> single purpose of trying to find the root cause?
>>>>>
>>>>> On Friday, June 5, 2015 at 5:12:43 AM UTC+2, Zongheng Yang wrote:
>>>>>>
>>>>>> Hi all,
>>>>>>
>>>>>> I'm using neo4j-import to import nodes and relationships from csv 
>>>>>> files. Let's say node id 538398 has about 100 edges and
>>>>>>
>>>>>> 538398 -> 370047
>>>>>> 538398 -> 379981
>>>>>>
>>>>>> are just two of them.  After the import, the neo4j database actually 
>>>>>>
>>>>>> - *loses* these two edges
>>>>>> - instead *corrupts* the destination ids, as follows
>>>>>>
>>>>>>     538398 -> 380047
>>>>>>     538398 -> 389981
>>>>>>
>>>>>> - *keeps* all other outgoing edges of 538398 correct
>>>>>>
>>>>>> The problem seems to be non-deterministic: doing a `rm -rf dbPath` 
>>>>>> and re-running neo4j-import seems to fix the issue, for this particular 
>>>>>> node -- but I've not done extensive tests to see whether other nodes get 
>>>>>> corrupted in this way.
>>>>>>
>>>>>> Has anyone seen this before? The graph has on the order of 1 million 
>>>>>> node, average degree 40. 
>>>>>>
>>>>>> Zongheng
>>>>>>
>>>>>
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