I see Shuyi's point that it would nice to allow adding jar files which
should be part of the user code classloader programmatically. Actually, we
expose this functionality in the `RemoteEnvironment` where you can specify
additional jars which shall be shipped to the cluster in the constructor. I
assume that is exactly the functionality you are looking for. In that
sense, it might be an API inconsistency that we allow it for some cases and
for others not.
But I could also see that the whole functionality of dynamically loading
jars at runtime could also perfectly live in the `UdfSqlOperator`. This, of
course, would entail that one has to take care of clean up of the
downloaded resources. But it should be possible to first download the
resources and create a custom URLClassLoader at startup and then use this
class loader when calling into the UDF.
Cheers,
Till
On Wed, May 16, 2018 at 9:28 PM, Shuyi Chen <suez1...@gmail.com> wrote:
> Hi Aljoscha, Fabian, Rong, Ted and Timo,
>
> Thanks a lot for the feedback. Let me clarify the usage scenario in a bit
> more detail. The context is that we want to add support for SQL DDL to load
> UDF from external JARs located either in local filesystem or HDFS or a HTTP
> endpoint in Flink SQL. The local FS option is more for debugging purpose
> for user to submit the job jar locally, and the later 2 are for production
> uses. Below is an example User application with the *CREATE FUNCTION* DDL
> (Note: grammar and interface not finalized yet).
>
> ------------------------------------------------------------
> -------------------------------------
>
>
>
>
> *val env = StreamExecutionEnvironment.getExecutionEnvironmentval tEnv =
> TableEnvironment.getTableEnvironment(env)// setup the DataStream//......*
>
>
>
>
>
>
>
>
>
>
>
> *// register the DataStream under the name
> "OrderAtEnv.registerDataStream("OrderA", orderA, 'user, 'product,
> 'amount)tEnv.sqlDDL( "create function helloFunc as
> 'com.example.udf.HelloWorld' using jars
> ('hdfs:///users/david/libraries/my-udf-1.0.1-SNAPSHOT.jar')")val result =
> tEnv.sqlQuery( "SELECT user, helloFunc(product), amount FROM OrderA WHERE
> amount > 2")result.toAppendStream[Order].print()env.execute()*
> ------------------------------------------------------------
> -------------------------------------
>
> The example application above does the following:
> 1) it registers a DataStream as a Calcite table(
> *org.apache.calcite.schema.Table*) under name "OrderA", so SQL can
> reference the DataStream as table "OrderA".
> 2) it uses the SQL *CREATE FUNCTION* DDL (grammar and interface not
> finalized yet) to create a SQL UDF called *helloFunc* from a JAR located in
> a remote HDFS path.
> 3) it issues a sql query that uses the *helloFunc* UDF defined above and
> generate a Flink table (*org.apache.flink.table.api.Table*)
> 4) it convert the Flink table back to a DataStream and print it.
>
> Step 1), 3), and 4) are already implemented. To implement 2), we need to do
> the following to implement the *tEnv.sqlDDL()* function.
>
> a) parse the DDL into a SqlNode to extract the UDF *udfClasspath*, UDF
> remote path *udfUrls[]* and UDF SQL name *udfName*.
> b) use the URLClassLoader to load the JARs specified in *udfUrls[]*, and
> register the SQL UDF using the {Batch/Stream/}TableEnvironment
> registerFunction methods using* udfClasspath* under name *udfName.*
> c) register the JARs *udfUrls[]* through the {Stream}ExecutionEnvironment,
> so that the JARs can be distributed to all the TaskManagers during runtime.
>
>
> Since the CREATE FUNCTION DDL is executed within the user application, I
> dont think we have access to the ClusterClient at the point when
> *tEnv.sqlDDL()* is executed. Also the JARs can be in a remote filesystem
> (which is the main usage scenarios), so the user can't really prepare the
> jar somehow in advance statically.
>
> For normal user application, I think {Stream}ExecutionEnvironment is the
> right place for the functionality, since it provides methods to control the
> job execution and to interact with the outside world, and also, it actually
> already does similar things provided through the *registerCachedFile*
> interface.
>
> However, in such case, SQL FUNCTION DDL and SQL client will use 2 different
> routes to register UDF jars, one through *JobGraph.jobConfiguration* and
> the other through *JobGraph.userJars*. So *maybe we can, as Fabian
> suggests, add **registerUserJarFile()/getUserJarFiles() interfaces
> in {Stream}ExecutionEnvironment, which stores the jars internally in a
> List, and when generating JobGraph, copy the jars to the JobGraph using
> the {Stream}ExecutionEnvironment.getUserJarFiles() and
> JobGraph.addJar()* (Note,
> streaming and batch implementations might vary). In such case, both SQL
> FUNCTION DDL and SQL client will use *JobGraph.userJars* to ship the UDF
> jars.
>
> Hope that clarifies better. What do you guys think? Thanks a lot.
>
> Cheers!
> Shuyi
>
> On Wed, May 16, 2018 at 9:45 AM, Rong Rong <walter...@gmail.com> wrote:
>
> > I think the question here is whether registering Jar files (or other
> > executable files) during job submission is sufficient for @shuyi's use
> > case.
> >
> > If I understand correctly regarding the part of dynamic distribution of
> the
> > external libraries in runtime. This is used to deal with DDL/DSL such as:
> > CREATE FUNCTION my_fun FROM url://<some_remote_jar>
> > during execution. Correct me if I am wrong @shuyi, The basic assumption
> > that "we can locate and ship all executable JARs during job submission"
> no
> > longer holds for your use case right?
> >
> > I guess we are missing details here regarding the "distribution of
> external
> > libraries in runtime" part. Maybe you can share more example of this use
> > case. Would this be included in the design doc @Timo?
> >
> > --
> > Rong
> >
> > On Wed, May 16, 2018 at 5:41 AM, Timo Walther <twal...@apache.org>
> wrote:
> >
> > > Yes, we are using the addJar functionionality of the JobGraph as well
> for
> > > the SQL Client.
> > >
> > > I think the execution environment is not the right place to specify
> jars.
> > > The location of the jars depends on the submission method. If a local
> > path
> > > is specified in the main() method of a packaged Flink jar, it would not
> > > work when such a program is submitted through the REST API.
> > >
> > > Regards,
> > > Timo
> > >
> > > Am 16.05.18 um 14:32 schrieb Aljoscha Krettek:
> > >
> > > I think this functionality is already there, we just have to expose it
> in
> > >> the right places: ClusterClient.submitJob() takes a JobGraph, JobGraph
> > has
> > >> method addJar() for adding jars that need to be in the classloader for
> > >> executing a user program.
> > >>
> > >> On 16. May 2018, at 12:34, Fabian Hueske <fhue...@gmail.com> wrote:
> > >>>
> > >>> Hi Ted,
> > >>>
> > >>> The design doc is in late draft status and proposes support for SQL
> DDL
> > >>> statements (CREATE TABLE, CREATE FUNCTION, etc.).
> > >>> The question about registering JARs came up because we need a way to
> > >>> distribute JAR files that contain the code of user-defined functions.
> > >>>
> > >>> The design doc will soon be shared on the dev mailing list to gather
> > >>> feedback from the community.
> > >>>
> > >>> Best, Fabian
> > >>>
> > >>> 2018-05-16 10:45 GMT+02:00 Ted Yu <yuzhih...@gmail.com>:
> > >>>
> > >>> bq. In a design document, Timo mentioned that we can ship multiple
> JAR
> > >>>> files
> > >>>>
> > >>>> Mind telling us where the design doc can be retrieved ?
> > >>>>
> > >>>> Thanks
> > >>>>
> > >>>> On Wed, May 16, 2018 at 1:29 AM, Fabian Hueske <fhue...@gmail.com>
> > >>>> wrote:
> > >>>>
> > >>>> Hi,
> > >>>>>
> > >>>>> I'm not sure if we need to modify the existing method.
> > >>>>> What we need is a bit different from what registerCachedFile()
> > >>>>> provides.
> > >>>>> The method ensures that a file is copied to each TaskManager and
> can
> > be
> > >>>>> locally accessed from a function's RuntimeContext.
> > >>>>> In our case, we don't need to access the file but would like to
> make
> > >>>>> sure
> > >>>>> that it is loaded into the class loader.
> > >>>>> So, we could also just add a method like registerUserJarFile().
> > >>>>>
> > >>>>> In a design document, Timo mentioned that we can ship multiple JAR
> > >>>>> files
> > >>>>> with a job.
> > >>>>> So, we could also implement the UDF shipping logic by loading the
> Jar
> > >>>>> file(s) to the client and distribute them from there.
> > >>>>> In that case, we would not need to add new method to the execution
> > >>>>> environment.
> > >>>>>
> > >>>>> Best,
> > >>>>> Fabian
> > >>>>>
> > >>>>> 2018-05-15 3:50 GMT+02:00 Rong Rong <walter...@gmail.com>:
> > >>>>>
> > >>>>> +1. This could be very useful for "dynamic" UDF.
> > >>>>>>
> > >>>>>> Just to clarify, if I understand correctly, we are tying to use an
> > >>>>>> ENUM
> > >>>>>> indicator to
> > >>>>>> (1) Replace the current Boolean isExecutable flag.
> > >>>>>> (2) Provide additional information used by ExecutionEnvironment to
> > >>>>>>
> > >>>>> decide
> > >>>>
> > >>>>> when/where to use the DistributedCached file.
> > >>>>>>
> > >>>>>> In this case, DistributedCache.CacheType or
> > DistributedCache.FileType
> > >>>>>> sounds more intuitive, what do you think?
> > >>>>>>
> > >>>>>> Also, I was wondering is there any other useful information for
> the
> > >>>>>>
> > >>>>> cached
> > >>>>>
> > >>>>>> file to be passed to runtime.
> > >>>>>> If we are just talking about including the library to the
> > classloader,
> > >>>>>>
> > >>>>> can
> > >>>>>
> > >>>>>> we directly extend the interface with
> > >>>>>>
> > >>>>>> public void registerCachedFile(
> > >>>>>> String filePath,
> > >>>>>> String name,
> > >>>>>> boolean executable,
> > >>>>>> boolean includeInClassLoader)
> > >>>>>>
> > >>>>>>
> > >>>>>> Thanks,
> > >>>>>> Rong
> > >>>>>>
> > >>>>>> On Sun, May 13, 2018 at 11:14 PM, Shuyi Chen <suez1...@gmail.com>
> > >>>>>>
> > >>>>> wrote:
> > >>>>
> > >>>>> Hi Flink devs,
> > >>>>>>>
> > >>>>>>> In an effort to support loading external libraries and creating
> > UDFs
> > >>>>>>>
> > >>>>>> from
> > >>>>>
> > >>>>>> external libraries using DDL in Flink SQL, we want to use Flink’s
> > >>>>>>>
> > >>>>>> Blob
> > >>>>
> > >>>>> Server to distribute the external libraries in runtime and load
> those
> > >>>>>>> libraries into the user code classloader automatically.
> > >>>>>>>
> > >>>>>>> However, the current [Stream]ExecutionEnvironment.
> > registerCachedFile
> > >>>>>>> interface limits only to registering executable or non-executable
> > >>>>>>>
> > >>>>>> blobs.
> > >>>>>
> > >>>>>> It’s not possible to tell in runtime if the blob files are
> libraries
> > >>>>>>>
> > >>>>>> and
> > >>>>>
> > >>>>>> should be loaded into the user code classloader in RuntimeContext.
> > >>>>>>> Therefore, I want to propose to add an enum called *BlobType*
> > >>>>>>>
> > >>>>>> explicitly
> > >>>>>
> > >>>>>> to
> > >>>>>>
> > >>>>>>> indicate the type of the Blob file being distributed, and the
> > >>>>>>>
> > >>>>>> following
> > >>>>
> > >>>>> interface in [Stream]ExecutionEnvironment to support it. In
> general,
> > >>>>>>>
> > >>>>>> I
> > >>>>
> > >>>>> think the new BlobType information can be used by Flink runtime to
> > >>>>>>> preprocess the Blob files if needed.
> > >>>>>>>
> > >>>>>>> */***
> > >>>>>>> ** Registers a file at the distributed cache under the given
> name.
> > >>>>>>>
> > >>>>>> The
> > >>>>
> > >>>>> file
> > >>>>>>
> > >>>>>>> will be accessible*
> > >>>>>>> ** from any user-defined function in the (distributed) runtime
> > under
> > >>>>>>>
> > >>>>>> a
> > >>>>
> > >>>>> local path. Files*
> > >>>>>>> ** may be local files (as long as all relevant workers have
> access
> > to
> > >>>>>>>
> > >>>>>> it),
> > >>>>>>
> > >>>>>>> or files in a distributed file system.*
> > >>>>>>> ** The runtime will copy the files temporarily to a local cache,
> if
> > >>>>>>> needed.*
> > >>>>>>> ***
> > >>>>>>> ** <p>The {@link org.apache.flink.api.common.
> > >>>>>>>
> > >>>>>> functions.RuntimeContext}
> > >>>>
> > >>>>> can
> > >>>>>>
> > >>>>>>> be obtained inside UDFs via*
> > >>>>>>> ** {@link
> > >>>>>>> org.apache.flink.api.common.functions.RichFunction#
> > >>>>>>>
> > >>>>>> getRuntimeContext()}
> > >>>>>
> > >>>>>> and
> > >>>>>>> provides access*
> > >>>>>>> ** {@link org.apache.flink.api.common.ca
> > >>>>>>> <http://org.apache.flink.api.common.ca>che.DistributedCache}
> via*
> > >>>>>>> ** {@link
> > >>>>>>> org.apache.flink.api.common.functions.RuntimeContext#
> > >>>>>>> getDistributedCache()}.*
> > >>>>>>> ***
> > >>>>>>> ** @param filePath The path of the file, as a URI (e.g.
> > >>>>>>>
> > >>>>>> "file:///some/path"
> > >>>>>>
> > >>>>>>> or "hdfs://host:port/and/path")*
> > >>>>>>> ** @param name The name under which the file is registered.*
> > >>>>>>> ** @param blobType indicating the type of the Blob file*
> > >>>>>>> **/*
> > >>>>>>>
> > >>>>>>> *public void registerCachedFile(String filePath, String name,
> > >>>>>>> DistributedCache.BlobType blobType) {...}*
> > >>>>>>>
> > >>>>>>> Optionally, we can add another interface to register UDF Jars
> which
> > >>>>>>>
> > >>>>>> will
> > >>>>>
> > >>>>>> use the interface above to implement.
> > >>>>>>>
> > >>>>>>> *public void registerJarFile(String filePath, String name) {...}*
> > >>>>>>>
> > >>>>>>> The existing interface in the following will be marked
> deprecated:
> > >>>>>>>
> > >>>>>>> *public void registerCachedFile(String filePath, String name,
> > boolean
> > >>>>>>> executable) {...}*
> > >>>>>>>
> > >>>>>>> And the following interface will be implemented using the new
> > >>>>>>>
> > >>>>>> interface
> > >>>>
> > >>>>> proposed above with a EXECUTABLE BlobType:
> > >>>>>>>
> > >>>>>>> *public void registerCachedFile(String filePath, String name) {
> ...
> > >>>>>>>
> > >>>>>> }*
> > >>>>
> > >>>>> Thanks a lot.
> > >>>>>>> Shuyi
> > >>>>>>>
> > >>>>>>> "So you have to trust that the dots will somehow connect in your
> > >>>>>>>
> > >>>>>> future."
> > >>>>>
> > >>>>
> > >
> > >
> >
>
>
>
> --
> "So you have to trust that the dots will somehow connect in your future."
>
