Re: DataSourceWriter V2 Api questions

[Dilip Biswal]

This is a pretty big challenge in general for data sources -- for the vast majority of data stores, the boundary of a transaction is per client. That is, you can't have two clients doing writes and coordinating a single transaction. That's certainly the case for almost all relational databases. Spark, on the other hand, will have multiple clients (consider each task a client) writing to the same underlying data store.

 

DB>> Perhaps we can explore two-phase commit protocol (aka XA) for this ? Not sure how easy it is to implement this though :-)

 

Regards,
Dilip Biswal
Tel: 408-463-4980
dbis...@us.ibm.com

 

 

----- Original message -----
From: Reynold Xin <r...@databricks.com>
To: Ryan Blue <rb...@netflix.com>
Cc: ross.law...@gmail.com, dev <dev@spark.apache.org>
Subject: Re: DataSourceWriter V2 Api questions
Date: Mon, Sep 10, 2018 10:26 AM
 

I don't think the problem is just whether we have a starting point for write. As a matter of fact there's always a starting point for write, whether it is explicit or implicit.

 

This is a pretty big challenge in general for data sources -- for the vast majority of data stores, the boundary of a transaction is per client. That is, you can't have two clients doing writes and coordinating a single transaction. That's certainly the case for almost all relational databases. Spark, on the other hand, will have multiple clients (consider each task a client) writing to the same underlying data store.

 

On Mon, Sep 10, 2018 at 10:19 AM Ryan Blue <rb...@netflix.com> wrote:

Ross, I think the intent is to create a single transaction on the driver, write as part of it in each task, and then commit the transaction once the tasks complete. Is that possible in your implementation?

 

I think that part of this is made more difficult by not having a clear starting point for a write, which we are fixing in the redesign of the v2 API. That will have a method that creates a Write to track the operation. That can create your transaction when it is created and commit the transaction when commit is called on it.

 

rb

 

On Mon, Sep 10, 2018 at 9:05 AM Reynold Xin <r...@databricks.com> wrote:

Typically people do it via transactions, or staging tables.

 

 

On Mon, Sep 10, 2018 at 2:07 AM Ross Lawley <ross.law...@gmail.com> wrote:

Hi all,

 

I've been prototyping an implementation of the DataSource V2 writer for the MongoDB Spark Connector and I have a couple of questions about how its intended to be used with database systems. According to the Javadoc for DataWriter.commit():

 

"this method should still "hide" the written data and ask the DataSourceWriter at driver side to do the final commit via WriterCommitMessage"

 

Although, MongoDB now has transactions, it doesn't have a way to "hide" the data once it has been written. So as soon as the DataWriter has committed the data, it has been inserted/updated in the collection and is discoverable - thereby breaking the documented contract.

 

I was wondering how other databases systems plan to implement this API and meet the contract as per the Javadoc?

 

Many thanks

 

Ross

 

 

--

Ryan Blue

Software Engineer

Netflix

 

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