Hi,
How many MatchingJobs do you submit?
On Tue, Sep 13, 2016 at 12:29 PM, 胡永亮/Bob <hu...@neusoft.com> wrote:
> Hello, Vladislav <vldpyat...@gmail.com>
>
> The following is some code.
>
> ...
> IgniteCompute compute = ignite.compute();//.withAsync();
>
> compute.run(new MatchingJob(m_mapReadyDataPara));
> }
>
> private static class MatchingJob implements IgniteRunnable{
>
> private Map<String, Map<Long, std>> m_mapReadyData;
> private IgniteCache<String, Map<Long, List<baselink>>> mapMatchingData;
> *//This is a cache in Ignite cluster.*
> ...
>
> public void run() {
> ...
> Iterator<Entry<String, Map<Long, std>>> entryKeyIterator1 = m_
> mapReadyData.entrySet().iterator(); *//**m_mapReadyData is the input
> data, its size is 5000 for every job now.*
> Map<String, Map<Long, List<baselink>>> local_writeCache =
> new HashMap<String, Map<Long, List<baselink>>>();
> ...
> *//Then the job read detail data from m_mapReadyData, and compute.*
> while (entryKeyIterator1.hasNext()) {
> Entry<String, Map<Long, std>> eKey1 =
> entryKeyIterator1.next();
> String carKey = eKey1.getKey();
> Map<Long, std> value1 = eKey1.getValue();
>
> * //local node cache*
> Map<Long, List<baselink>> existMapbaselink = local_
> mapMatchingData.get(carKey);
> if(existMapbaselink == null){
> existMapbaselink = mapMatchingData.get(carKey); * //Read
> data to compute with it from Ignite cache. This data's size is 154M for *
> PARTITIONED *mode.*
> if(existMapbaselink != null)
> local_mapMatchingData.putIfAbsent(
> carKey, existMapbaselink);
> }
>
> * //some compute logic code*
>
> mapbaselink = local_writeCache.get(carKey);
> if(mapbaselink == null){
> mapbaselink = new TreeMap<Long, List<baselink>>();
> }
> mapbaselink.put(stdtime, ListBaseLink);
> local_writeCache.put(carKey, mapbaselink);
> }
>
> *//batch to write data into Ignite.*
> Iterator<Entry<String, Map<Long, List<baselink>>>> it = local_
> writeCache.entrySet().iterator();
> while(it.hasNext()){
> Entry<String, Map<Long, List<baselink>>>
> entry = it.next();
> String carKey = entry.getKey();
> final Map<Long, List<baselink>> value = entry.getValue();
>
> if(!mapMatchingData.containsKey(carKey)){
> mapMatchingData.put(carKey, value);
> }else{
> mapMatchingData.invoke(carKey,
> new EntryProcessor<String, Map<Long, List<baselink>>, Void>() {
> @Override
> public Void process(MutableEntry<
> String, Map<Long, List<baselink>>> entry, Object... args) {
> Map<Long, List<baselink>> map =
> entry.getValue();
> map.putAll(value);
> entry.setValue(map);
> return null;
> }
> });
> }
>
> }
>
>
> ------------------------------
> bob
>
>
> *From:* Vladislav Pyatkov <vldpyat...@gmail.com>
> *Date:* 2016-09-12 18:37
> *To:* user@ignite.apache.org
> *Subject:* Re: Increase Ignite instances can't increase the speed of
> compute
> Hello,
>
> I don't understand, what do you try to measure, without code.
> Size of calculation task, size of data moved into network have importance.
>
> Could you please provide code example?
>
> On Mon, Sep 12, 2016 at 12:33 PM, 胡永亮/Bob <hu...@neusoft.com> wrote:
>
>> Hi, everyone:
>>
>> I am using Ignite for computing and cache.
>>
>> I use the same input data and the same compute logic.
>> When my ignite cluster's node is 2 in 2 machines, the total cost time
>> is 38s.
>>
>> But, when I increase the Ignite cluster nodes to 3 in 3 machines, the
>> cost time is 32s/51s/41s
>> 4 instances in 4 machines, the cost time is 32s/40s.
>>
>> The compute speed can't change faster, what may the reason be?
>>
>> Thanks.
>>
>> Bob
>>
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>>
>
>
>
> --
> Vladislav Pyatkov
>
>
> ------------------------------------------------------------
> ---------------------------------------
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> of this communication is
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