Comments (1)
The pull and push methods return a scala Future. To attach callbacks to these futures we will need access to the execution context regardless. Therefor I think it is best to keep the execution context in the call.
To simplify the code a little bit, we can change the implicit timeout to a configurable property and remove it from the call API. The most recent version of the code uses a hand-shake protocol for push request, so the timeout property is largely ignored there anyway.
In the mean-time, I've written a very simple example about serialization with Spark in the documentation, that can be run very easily in the spark-shell: http://rjagerman.github.io/glint/gettingstarted/spark/
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Related Issues (20)
- Actor Not Found
- Can glint support SSP mode HOT 3
- PullFailedException in large dataset HOT 8
- Implementation bug in ColumnIterator? HOT 15
- A question about glint HOT 4
- Rework of Glint internals HOT 7
- Struggling with data transfer / actor disassociated HOT 5
- Not able to pull matrix slice with rows != cols HOT 5
- Look into Akka Artery
- Random init HOT 1
- why make "push" as an “accumulator” rather than “replacer”? HOT 6
- BigMatrix should support push(rows)
- Can glint support BigInt type? HOT 1
- Does glint support (key, value) store ? HOT 1
- BigMatrix push and pull is high network consumption HOT 1
- Can not create Glint Client in Apache Spark HOT 4
- Akka Actor Error when initializing Glint Client HOT 2
- cluster conf example
- Got runtime issues when using spark-shell HOT 2
- Need Save Operation to store the big vector/matrix into HDFS HOT 1
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