[infinispan-dev] Major version cleaning

[Dan Berindei]

On Tue, Feb 21, 2017 at 8:28 PM, Radim Vansa <rvansa at redhat.com> wrote:
> On 02/21/2017 07:14 PM, Dan Berindei wrote:
>> But doesn't the functional API's evalMany() provide something very
>> close to the API you're suggesting?
>>
>> Dan
>>
>>
>> On Tue, Feb 21, 2017 at 7:55 PM, Radim Vansa <rvansa at redhat.com> wrote:
>>> On 02/21/2017 05:16 PM, Tristan Tarrant wrote:
>>>> On 21/02/17 16:29, Sanne Grinovero wrote:
>>>>>> You haven't explained what "flush" means. Since you separate that from
>>>>>> atomicity/consistency, I assume that batches on non-tx cache are just
>>>>>> ordered putOrRemoveAll operations, immediately visible on flush without
>>>>>> any atomicity.
>>>> I assume that in Sanne's idea, ordering in a batch doesn't matter, aside
>>>> from operations on the same key. Having ordering in there would for
>>>> example not allow us to parallelize by segment.
>>>>
>>>>> So I want to write a first chunk, in our code that looks like:
>>>>>
>>>>> startBatch
>>>>> put(chunk1/A, [some large value])
>>>>> put(chunk1/B, [some small metadata])
>>>>> put(chunk1/C, [some small metadata])
>>>>> endBatch
>>>>> There is no reason to use a transaction, in fact we had to disable
>>>>> transactions as some of these entries could be large.
>>>>> There also is no reason for the batch, other than optimising the latency.
>>>> Let me summarize to see if we have the requirements for a useful
>>>> batching system (which is sort of patterned on the JDBC statement batching):
>>>>
>>>> - a batch is not an atomic operation, i.e. it is not backed by a transaction
>>>> - it can be wrapped in a transaction if needed
>>>> - batches cannot be nested
>>>> - batches only involve unconditional write operations (put, putAll, remove)
>>>> - ordering of operations within a batch is unimportant aside from
>>>> modifications to the same key where we apply "last one wins"
>>>> - when a batch is "flushed" (i.e. endBatch is invoked) the ops are
>>>> grouped by segment and sent to the appropriate owner for processing,
>>>> potentially in parallel
>>>>
>>>> As Radim has called it, this is essentially a putOrRemoveAll op (with an
>>>> async counterpart).
>>> It is putOrRemoveAll when applied on a non-tx cache, and actually
>>> implementing that shouldn't be complex. However, when transactions come
>>> into play, it is different, because Sanne wants us to remove the
>>> modifications in completed batch from the local transactional invocation
>>> context and 'cache' them on the owners. Since reads have to be
>>> transactionally consistent, we need to inspect the transaction on the
>>> remote nodes (remote repeatable read).
>>>
>>> Sanne's request makes sense to me. However as the current implementation
>>> is providing a false assumption that it could work as JDBC batches while
>>> it's nothing but crippled JTA, and as I don't see anyone shouting "I'll
>>> implement that, next week it's done!", I second deprecating/removing the
>>> API for the time being.
>>>
>> Exactly my thoughts, it's definitely not an unreasonable request, but
>> it would require a lot of work to implement correctly.
>>
>>
>>> I don't find the current API ideal either, as it depends on thread
>>> locals (JTA does as well, but...) while it does not seem useful enough
>>> to me. I would prefer
>>>
>>> interface BatchingCache {
>>>       Batch start();
>>> }
>>>
>>> @NotThreadSafe
>>> interface Batch {
>>>       void put(K k, V value);
>>>       ...
>>>       void execute();
>>>       void drop(); // maybe not needed
>>> }
>>>
>> I was hoping the functional API's evalMany() would be good enough, but
>> I see now that it replicates the function argument (which holds all
>> the values) everywhere. So putAll() is still more efficient, unless
>> using groups to make sure all keys in the batch have the same owners.
>
> Uh, doesn't putAll do the same? Is the modifications list isolate per
> target segments when replicating?
>

I missed the evalMany(Map, BiFunction) overload yesterday, and I
assume WriteOnlyMap.evalMany(Map,
MarshallableFunctions.setValueConsumer()) would behave exactly the
same as putAll(Map). Of course, it's not better either, as you still
have to create the map beforehand...

OTOH I'm pretty sure you're the one who wrote the code to split the
input keys/values by target segments both for putAll() and for
evalMany() in NonTxDistributionInterceptor :)

Dan