Clojure API for a more dynamic Google Cloud Dataflow and (not really battle tested) any other Apache Beam backend.
You can also see ports of the official Dataflow examples in the
datasplash.examples
namespace.
Here is the classic word count example.
ℹ️ You will need to run (compile 'datasplash.examples)
every time you make a change.
(ns datasplash.examples
(:require [clojure.string :as str]
[datasplash.api :as ds]
[datasplash.options :refer [defoptions]])
(:gen-class))
(defn tokenize
[^String l]
(remove empty? (.split (str/trim l) "[^a-zA-Z']+")))
(defn count-words
[p]
(ds/->> :count-words p
(ds/mapcat tokenize {:name :tokenize})
(ds/frequencies)))
(defn format-count
[[k v]]
(format "%s: %d" k v))
(defoptions WordCountOptions
{:input {:default "gs://dataflow-samples/shakespeare/kinglear.txt"
:type String}
:output {:default "kinglear-freqs.txt" :type String}
:numShards {:default 0 :type Long}})
(defn -main
[& str-args]
(let [p (ds/make-pipeline WordCountOptions str-args)
{:keys [input output numShards]} (ds/get-pipeline-options p)]
(->> p
(ds/read-text-file input {:name "King-Lear"})
(count-words)
(ds/map format-count {:name :format-count})
(ds/write-text-file output {:num-shards numShards})
(ds/run-pipeline))))
Locally on your machine using a DirectRunner:
(in-ns 'datasplash.examples)
(clojure.core/compile 'datasplash.examples)
(-main "--input=sometext.txt" "--output=out-freq.txt" "--numShards=1")
Remotely on Google Cloud using a DataflowRunner:
You should have properly configured your Google Cloud account and Dataflow access from your machine.
(in-ns 'datasplash.examples)
(clojure.core/compile 'datasplash.examples)
(-main "--project=my-project"
"--runner=DataflowRunner"
"--gcpTempLocation=gs://bucket/tmp"
"--input=gs://apache-beam-samples/shakespeare/kinglear.txt"
"--output=gs://bucket/outputs/kinglear-freq.txt"
"--numShards=1")
Datasplash needs to be AOT compiled, so you should prepare an uberjar and run from your main entry like so:
java -jar my-dataflow-job-uber.jar [beam-args]
- Due to the way the code is loaded when running in distributed mode, you may
get some exceptions about unbound vars, especially when using instances with
a high number of cpu. They will not however cause the job to fail and are of
no consequences. They are caused by the need to prep the Clojure runtime when
loading the class files in remote instances and some tricky business with
locks and
require
. - If you have to write your own low-level
ParDo
objects (you shouldn't), wrap all your code in thesafe-exec
macro to avoid issues with unbound vars. Any good idea about finding a better way to do this would be greatly appreciated! - If some of the
UserCodeException
as seen in the cloud UI are mangled and missing the relevant part of the Clojure source code, this is due to a bug with the way the sdk mangles stacktraces in Clojure. In this case look for ClojureRuntimeException in the logs to find the original unaltered stacktrace. - Beware of using Clojure 1.9:
proxy
results are notSerializable
anymore, so you cannot use anywhere in your pipeline Clojure code that uses proxy. Use Java shim for these objects instead. - If you see something like
java.lang.ClassNotFoundException: Options
you probably forgot to compile your namespace. - Whenever you need to check some spec in user code, you will have to first require
those specs because they may not be loaded in your Clojure runtime. But don't
use
(require)
because it's not thread safe. See [this issue] for a workaround. - If you see a
java.io.IOException: No such file or directory
when invokingcompile
, make sure there is a directory in your project root that matches the value of*compile-path*
(defaultclasses
).
The Beam Java SDK does not pull in the Zstd library by default, so it is the
user's responsibility to declare an explicit dependency on zstd-jni
. Attempts
to read or write .zst files without this library loaded will result in
NoClassDefFoundError
at runtime.
The Beam Java SDK does not pull in the required libraries for LZOP compression
by default, so it is the user's responsibility to declare an explicit
dependency on io.airlift:aircompressor
and
com.facebook.presto.hadoop:hadoop-apache2
. Attempts to read or write .lzo
files without those libraries loaded will result in a NoClassDefFoundError
at runtime.
See Apache Beam Compression enum for details.
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