storm集群上运行的是一个个topology，一个topology是spouts和bolts组成的图。当我们开发完topology程序后将其打成jar包，然后在shell中执行storm jar xxxxxx.jar xxxxxxxClass就可以将jar包上传到storm集群的nimbus上，并执行topology。本文主要分析下topology的jar包是如何上传到nimbus上的。首先我们从storm的jar命令入手，jar命令的实现位于storm根目录的bin/storm文件里。定义如下：
"""Syntax: [storm jar topology-jar-path class ...]
Runs the main method of class with the specified arguments.
The storm jars and configs in ~/.storm are put on the classpath.
The process is configured so that StormSubmitter
(http://nathanmarz.github.com/storm/doc/backtype/storm/StormSubmitter.html)
will upload the jar at topology-jar-path when the topology is submitted.
"""
exec_storm_class(
klass,
jvmtype="-client",
extrajars=[jarfile, USER_CONF_DIR, STORM_DIR + "/bin"],
args=args,
jvmopts=[' '.join(filter(None, [JAR_JVM_OPTS, "-Dstorm.jar=" + jarfile]))])
jar命令是由python实现的，很奇怪为什么不用clojure实现呢？（不得而知）。jarfile表示jar包的位置；klass表示topology的入口，也就是有main函数的类；*args表示传递给main函数的参数。jvmtype="-client"表示指定jvm类型为client类型（jvm有两种类型client和server，服务器端默认为server类型）；extrajars集合用于存放编译topology的jar包时，所有依赖jar包的路径；jvmopts集合存放以jvm参数，这里比较重要的是-Dstorm.jar参数，这个参数的值是jarfile，这样在运行submitTopology方法时就可以通过storm.jar参数获得jar包的路径了（通过jvm参数进行方法参数传递）exec_storm_class函数的逻辑比较简单，具体实现如下：
global CONFFILE
all_args = [
"java", jvmtype, get_config_opts(),
"-Dstorm.home=" + STORM_DIR,
"-Djava.library.path=" + confvalue("java.library.path", extrajars),
"-Dstorm.conf.file=" + CONFFILE,
"-cp", get_classpath(extrajars),
] + jvmopts + [klass] + list(args)
print "Running: " + " ".join(all_args)
if fork:
os.spawnvp(os.P_WAIT, "java", all_args)
else:
os.execvp("java", all_args) # replaces the current process and never returns
get_config_opts()获取jvm的默认配置信息，confvalue("java.library.path", extrajars)获取storm使用的本地库JZMQ加载路径，get_classpath(extrajars)获取所有依赖jar包的完整路径，然后拼接一个java -cp命令运行topology的main方法。接下来程序执行流程转移到topology的main方法内，我们以storm-starter项目中的wordCountTopology的main方法为例：
TopologyBuilder builder = new TopologyBuilder();
builder.setSpout("spout", new RandomSentenceSpout(), 6);
builder.setBolt("split", new SplitSentence(), 12).shuffleGrouping("spout");
builder.setBolt("count", new WordCount(), 10).fieldsGrouping("split", new Fields("word"));
Config conf = new Config();
conf.setDebug(true);
if (args != null && args.length > 0) {
conf.setNumWorkers(4);
StormSubmitter.submitTopology(args[0], conf, builder.createTopology());
}
else {
conf.setMaxTaskParallelism(3);
LocalCluster cluster = new LocalCluster();
cluster.submitTopology("word-count", conf, builder.createTopology());
Thread.sleep(10000);
cluster.shutdown();
}
}
main方法构建topology后，调用StormSubmitter类的submitTopology方法提交topology。submitTopology方法如下：
* Submits a topology to run on the cluster. A topology runs forever or until
* explicitly killed.
*
*
* @param name the name of the storm.
* @param stormConf the topology-specific configuration. See {@link Config}.
* @param topology the processing to execute.
* @throws AlreadyAliveException if a topology with this name is already running
* @throws InvalidTopologyException if an invalid topology was submitted
*/
public static void submitTopology(String name, Map stormConf, StormTopology topology)
throws AlreadyAliveException, InvalidTopologyException {
submitTopology(name, stormConf, topology, null);
}
/**
* Submits a topology to run on the cluster. A topology runs forever or until
* explicitly killed.
*
*
* @param name the name of the storm.
* @param stormConf the topology-specific configuration. See {@link Config}.
* @param topology the processing to execute.
* @param options to manipulate the starting of the topology
* @throws AlreadyAliveException if a topology with this name is already running
* @throws InvalidTopologyException if an invalid topology was submitted
*/
public static void submitTopology(String name, Map stormConf, StormTopology topology, SubmitOptions opts)
throws AlreadyAliveException, InvalidTopologyException {
if(!Utils.isValidConf(stormConf)) {
throw new IllegalArgumentException("Storm conf is not valid. Must be json-serializable");
}
stormConf = new HashMap(stormConf);
stormConf.putAll(Utils.readCommandLineOpts());
Map conf = Utils.readStormConfig();
conf.putAll(stormConf);
try {
String serConf = JSONValue.toJSONString(stormConf);
if(localNimbus!=null) {
LOG.info("Submitting topology " + name + " in local mode");
localNimbus.submitTopology(name, null, serConf, topology);
} else {
NimbusClient client = NimbusClient.getConfiguredClient(conf);
if(topologyNameExists(conf, name)) {
throw new RuntimeException("Topology with name `" + name + "` already exists on cluster");
}
submitJar(conf);
try {
LOG.info("Submitting topology " + name + " in distributed mode with conf " + serConf);
if(opts!=null) {
client.getClient().submitTopologyWithOpts(name, submittedJar, serConf, topology, opts);
} else {
// this is for backwards compatibility
client.getClient().submitTopology(name, submittedJar, serConf, topology);
}
} catch(InvalidTopologyException e) {
LOG.warn("Topology submission exception", e);
throw e;
} catch(AlreadyAliveException e) {
LOG.warn("Topology already alive exception", e);
throw e;
} finally {
client.close();
}
}
LOG.info("Finished submitting topology: " + name);
} catch(TException e) {
throw new RuntimeException(e);
}
}
submitTopology方法主要完成三件工作：
1. 配置参数
把命令行参数放在stormConf, 从conf/storm.yaml读取配置参数到conf, 再把stormConf也put到conf, 可见命令行参数的优先级更高，将stormConf转化为Json, 因为这个配置是要发送到服务器的
2. 调用submitJar方法
private static void submitJar(Map conf) {
if(submittedJar==null) {
LOG.info("Jar not uploaded to master yet. Submitting jar...");
String localJar = System.getProperty("storm.jar");
submittedJar = submitJar(conf, localJar);
} else {
LOG.info("Jar already uploaded to master. Not submitting jar.");
}
}
System.getProperty("storm.jar")获取jvm参数storm.jar的值，即topology jar包的路径，然后调用重载方法submitJar。
if(localJar==null) {
throw new RuntimeException("Must submit topologies using the 'storm' client script so that StormSubmitter knows which jar to upload.");
}
NimbusClient client = NimbusClient.getConfiguredClient(conf);
try {
String uploadLocation = client.getClient().beginFileUpload();
LOG.info("Uploading topology jar " + localJar + " to assigned location: " + uploadLocation);
BufferFileInputStream is = new BufferFileInputStream(localJar);
while(true) {
byte[] toSubmit = is.read();
if(toSubmit.length==0) break;
client.getClient().uploadChunk(uploadLocation, ByteBuffer.wrap(toSubmit));
}
client.getClient().finishFileUpload(uploadLocation);
LOG.info("Successfully uploaded topology jar to assigned location: " + uploadLocation);
return uploadLocation;
} catch(Exception e) {
throw new RuntimeException(e);
} finally {
client.close();
}
}
StormSubmitter的本质是个Thrift Client，而Nimbus则是Thrift Server，所以所有的操作都是通过Thrift RPC来完成，submitJar首先创建client，然后调用nimbus thrift server的beginFileUpload()方法获取nimbus存放jar的目录。beginFileUpload函数如下：
(let [fileloc (str (inbox nimbus) "/stormjar-" (uuid) ".jar")]
(.put (:uploaders nimbus)
fileloc
(Channels/newChannel (FileOutputStream. fileloc)))
(log-message "Uploading file from client to " fileloc)
fileloc
))
(inbox nimbus)函数里面又调用了master-inbox函数，master-inbox主要创建storm.local.dir的值/inbox目录，并返回完整目录名，所以topology jar包的将会通过uploadChunk方法上传到nimbus上的storm.local.dir的值/inbox/stormjar-32位uuid.jar。
3. 生成thrift client并调用nimbus thrift server的submitTopologyWithOpts或submitTopology方法(submitTopologyWithOpts或submitTopology方法定义在Nimbus.clj中)，submitTopologyWithOpts如下：
[this ^String storm-name ^String uploadedJarLocation ^String serializedConf ^StormTopology topology
^SubmitOptions submitOptions]
(try
(assert (not-nil? submitOptions))
(validate-topology-name! storm-name)
(check-storm-active! nimbus storm-name false)
(let [topo-conf (from-json serializedConf)]
(try
(validate-configs-with-schemas topo-conf)
(catch IllegalArgumentException ex
(throw (InvalidTopologyException. (.getMessage ex)))))
(.validate ^backtype.storm.nimbus.ITopologyValidator (:validator nimbus)
storm-name
topo-conf
topology))
(swap! (:submitted-count nimbus) inc)
(let [storm-id (str storm-name "-" @(:submitted-count nimbus) "-" (current-time-secs))
storm-conf (normalize-conf
conf
(-> serializedConf
from-json
(assoc STORM-ID storm-id)
(assoc TOPOLOGY-NAME storm-name))
topology)
total-storm-conf (merge conf storm-conf)
topology (normalize-topology total-storm-conf topology)
storm-cluster-state (:storm-cluster-state nimbus)]
(system-topology! total-storm-conf topology) ;; this validates the structure of the topology
(log-message "Received topology submission for " storm-name " with conf " storm-conf)
;; lock protects against multiple topologies being submitted at once and
;; cleanup thread killing topology in b/w assignment and starting the topology
(locking (:submit-lock nimbus)
(setup-storm-code conf storm-id uploadedJarLocation storm-conf topology)
(.setup-heartbeats! storm-cluster-state storm-id)
(let [thrift-status->kw-status {TopologyInitialStatus/INACTIVE :inactive
TopologyInitialStatus/ACTIVE :active}]
(start-storm nimbus storm-name storm-id (thrift-status->kw-status (.get_initial_status submitOptions))))
(mk-assignments nimbus)))
(catch Throwable e
(log-warn-error e "Topology submission exception. (topology name='" storm-name "')")
(throw e))))
storm-name表示topology的名字，uploadedJarLocation表示jar包在nimbus上的位置，serializedConf表示topology的序列化的配置信息，topology参数表示thrift结构的topology，topology结构定义在storm.thrift中，如下：
//ids must be unique across maps
// #workers to use is in conf
1: required map<string, SpoutSpec> spouts;
2: required map<string, Bolt> bolts;
3: required map<string, StateSpoutSpec> state_spouts;
}
spouts存放spout id和spout的键值对，bolts存放bolt id和bolt的键值对，StateSpoutSpec暂未实现。SpoutSpec定义如下：
1: required ComponentObject spout_object;
2: required ComponentCommon common;
// can force a spout to be non-distributed by overriding the component configuration
// and setting TOPOLOGY_MAX_TASK_PARALLELISM to 1
}
Bolt定义如下：
1: required ComponentObject bolt_object;
2: required ComponentCommon common;
}
Bolt和Spout的结构相同，都是由1个ComponentObject结构和1个ComponentCommon结构组成。ComponentObject定义如下：
1: binary serialized_java;
2: ShellComponent shell;
3: JavaObject java_object;
}
ComponentObject即是bolt的实现实体，它可以是以下三个类型之一：
1、1个序列化的java对象（这个对象实现IBolt接口）
2、1个ShellComponent对象，意味着bolt是由其他语言实现的。如果以这种方式来定义1个bolt，Storm将会实例化1个ShellBolt对象来
负责处理基于JVM的worker进程与非JVM的component(即该bolt)实现体之间的通讯。
3、1个JavaObject结构，这个结构告诉Storm实例化这个bolt所需要的classname和构造函数参数。这一点在你想用非JVM语言来定义topology时比较有用。这样，在你使用非JVM语言来定义topology时就可以做到既使用基于 JVM的spout或bolt，同时又不需要创建并序列化它们的Java对象。
ComponentCommon定义如下：
1: required map<GlobalStreamId, Grouping> inputs;
2: required map<string, StreamInfo> streams; //key is stream id
3: optional i32 parallelism_hint; //how many threads across the cluster should be dedicated to this component
// component specific configuration respects:
// topology.debug: false
// topology.max.task.parallelism: null // can replace isDistributed with this
// topology.max.spout.pending: null
// topology.kryo.register // this is the only additive one
// component specific configuration
4: optional string json_conf;
}
GlobalStreamId定义如下：
1: required string componentId;
2: required string streamId;
#Going to need to add an enum for the stream type (NORMAL or FAILURE)
}
ComponentCommon定义了这个component的其他所有属性。包括：
1、这个component接收什么stream（被定义在1个component_id到stream_id的map里，在stream做分组时用到）
2、这个component发射什么stream以及stream的元数据（是否是direct stream，stream中field的声明）
3、这个component的并行度
4、这个component的配置项configuration
(assert (not-nil? submitOptions))如果submitOptions为nil，那么assert将会抛出java.lang.AssertionError，(validate-topology-name! storm-name)验证topology的名字，validate-topology-name!定义如下：
(if (some #(.contains name %) DISALLOWED-TOPOLOGY-NAME-STRS)
(throw (InvalidTopologyException.
(str "Topology name cannot contain any of the following: " (pr-str DISALLOWED-TOPOLOGY-NAME-STRS))))
(if (clojure.string/blank? name)
(throw (InvalidTopologyException.
("Topology name cannot be blank"))))))
DISALLOWED-TOPOLOGY-NAME-STRS定义如下：
包含了不允许出现在topology名字中的特殊字符，some函数的第一个参数是一个匿名函数，对DISALLOWED-TOPOLOGY-NAME-STRS集合中的每个元素应用该匿名函数，遇到第一个true则返回true。validate-topology-name!函数主要检查topology的名字中是否包含"非法字符"。check-storm-active!函数用于检查该topology的状态是否是"active"。定义如下：
(if (= (not active?)
(storm-active? (:storm-cluster-state nimbus)
storm-name))
(if active?
(throw (NotAliveException. (str storm-name " is not alive")))
(throw (AlreadyAliveException. (str storm-name " is already active"))))
))
nimbus是一个保存了nimbus thrift server当前状态的map，这个map是由nimbus-data函数生成的，nimbus-data函数如下：
(let [forced-scheduler (.getForcedScheduler inimbus)]
{:conf conf
:inimbus inimbus
:submitted-count (atom 0)
:storm-cluster-state (cluster/mk-storm-cluster-state conf)
:submit-lock (Object.)
:heartbeats-cache (atom {})
:downloaders (file-cache-map conf)
:uploaders (file-cache-map conf)
:uptime (uptime-computer)
:validator (new-instance (conf NIMBUS-TOPOLOGY-VALIDATOR))
:timer (mk-timer :kill-fn (fn [t]
(log-error t "Error when processing event")
(exit-process! 20 "Error when processing an event")
))
:scheduler (mk-scheduler conf inimbus)
}))
conf保存了storm集群的配置信息，inimbus表示当前nimbus实例，cluster/mk-storm-cluster-state返回一个实现了StormClusterState协议的实例。storm-active?函数定义如下：
(not-nil? (get-storm-id storm-cluster-state storm-name)))
通过调用get-storm-id函数获取指定topology名字的topology id，如果id存在则返回true，否则返回false。get-storm-id函数如下：
(let [active-storms (.active-storms storm-cluster-state)]
(find-first
#(= storm-name (:storm-name (.storm-base storm-cluster-state % nil)))
active-storms)
))
active-storms函数获取zookeeper中/storms/的所有children，/storms/{topology-id}中存放当前正在运行的topology信息。保存的内容参考common.clj中的类StormBase。
find-first函数返回名字等于storm-name的第一个topology的id。当我们正确提交topology时，由于zookeeper中的/storms中不存在与之对应的{topology-id}文件，所以check-storm-active!函数的第一个if的条件表达式为(= true true)。进而通过check-storm-active!函数的检查。将topology的配置信息绑定到topo-conf，validate-configs-with-schemas函数验证配置信息的正确性，validate-configs-with-schemas定义如下：
[conf]
(doseq [[k v] conf
:let [schema (CONFIG-SCHEMA-MAP k)]]
(if (not (nil? schema))
(.validateField schema k v))))
CONFIG-SCHEMA-MAP定义如下：
;; Config fields must have a _SCHEMA field defined
(def CONFIG-SCHEMA-MAP
(->> (.getFields Config)
(filter #(not (re-matches #".*_SCHEMA$" (.getName %))))
(map (fn [f] [(.get f nil)
(get-FieldValidator
(-> Config
(.getField (str (.getName f) "_SCHEMA"))
(.get nil)))]))
(into {})))
Config.java中主要有两类静态变量：一类是配置信息，一类是配置信息对应的校验器，校验器属性以_SCHEMA结尾。CONFIG-SCHEMA-MAP中存放了配置信息变量名和对应校验器的键值对config-string -> validator。
validate-configs-with-schemas函数就是根据配置信息名获取对应校验器，然后对配置信息值进行校验。相关校验器请查看ConfigValidation类的内部类FieldValidator。(:validator nimbus)返回一个实现了backtype.storm.nimbus.ITopologyValidator接口的实例(backtype.storm.nimbus.DefaultTopologyValidators实例)并调用其validate方法。backtype.storm.nimbus.DefaultTopologyValidators类如下：
@Override
public void prepare(Map StormConf){
}
@Override
public void validate(String topologyName, Map topologyConf, StormTopology topology) throws InvalidTopologyException {
}
}
默认情况下validate方法是一个空实现。
swap!函数用于将atom(原子类型，与java中的原子类型相同)类型的(:submitted-count nimbus)加1，保存已提交topology的个数。storm-id绑定了topology的id。storm-conf绑定topology配置信息和集群配置信息合并后序列化器、需要序列化的类、acker的个数和最大任务并行度配置信息。total-storm-conf绑定全部配置信息。normalize-topology函数主要功能就是为topology添加"topology.tasks"（task总数）配置信息。
normalize-topology定义如下：
(let [ret (.deepCopy topology)]
(doseq [[_ component] (all-components ret)]
(.set_json_conf
(.get_common component)
(->> {TOPOLOGY-TASKS (component-parallelism storm-conf component)}
(merge (component-conf component))
to-json )))
ret ))
ret绑定一个topology的深度复制，all-components函数返回该topology的所有组件的id和spout/bolt对象的键值对，然后通过调用get_common方法获取spot/bolt对象的ComponentCommon属性，->>是clojure中的一个宏，作用就是将{......}作为merge函数的最后一个参数，然后将merge函数的返回值作为to-json函数的最后一个参数，component-parallelism函数定义如下:
(let [storm-conf (merge storm-conf (component-conf component))
num-tasks (or (storm-conf TOPOLOGY-TASKS) (num-start-executors component))
max-parallelism (storm-conf TOPOLOGY-MAX-TASK-PARALLELISM)
]
(if max-parallelism
(min max-parallelism num-tasks)
num-tasks)))
component-parallelism是个私有函数，主要功能就是确定"topology.tasks"的值，num-start-executors函数获取spout/bolt的并行度，没有设置并行度时默认值为1，num-tasks绑定该topology的任务数，max-parallelism绑定最大任务数，最后num-tasks和max-parallelism中较小的。normalize-topology函数会将添加了"topology.tasks"的配置信息保存到spout/bolt的ComponentCommon属性的json_conf中，并返回修改后的topology。
system-topology!函数定义如下：
(validate-basic! topology)
(let [ret (.deepCopy topology)]
(add-acker! storm-conf ret)
(add-metric-components! storm-conf ret)
(add-system-components! storm-conf ret)
(add-metric-streams! ret)
(add-system-streams! ret)
(validate-structure! ret)
ret
))
validate-basic!验证topology的基本信息，add-acker!添加acker bolt，add-acker!函数定义如下：
(let [num-executors (if (nil? (storm-conf TOPOLOGY-ACKER-EXECUTORS)) (storm-conf TOPOLOGY-WORKERS) (storm-conf TOPOLOGY-ACKER-EXECUTORS))
acker-bolt (thrift/mk-bolt-spec* (acker-inputs ret)
(new backtype.storm.daemon.acker)
{ACKER-ACK-STREAM-ID (thrift/direct-output-fields ["id"])
ACKER-FAIL-STREAM-ID (thrift/direct-output-fields ["id"])
}
:p num-executors
:conf {TOPOLOGY-TASKS num-executors
TOPOLOGY-TICK-TUPLE-FREQ-SECS (storm-conf TOPOLOGY-MESSAGE-TIMEOUT-SECS)})]
(dofor [[_ bolt] (.get_bolts ret)
:let [common (.get_common bolt)]]
(do
(.put_to_streams common ACKER-ACK-STREAM-ID (thrift/output-fields ["id" "ack-val"]))
(.put_to_streams common ACKER-FAIL-STREAM-ID (thrift/output-fields ["id"]))
))
(dofor [[_ spout] (.get_spouts ret)
:let [common (.get_common spout)
spout-conf (merge
(component-conf spout)
{TOPOLOGY-TICK-TUPLE-FREQ-SECS (storm-conf TOPOLOGY-MESSAGE-TIMEOUT-SECS)})]]
(do
;; this set up tick tuples to cause timeouts to be triggered
(.set_json_conf common (to-json spout-conf))
(.put_to_streams common ACKER-INIT-STREAM-ID (thrift/output-fields ["id" "init-val" "spout-task"]))
(.put_to_inputs common
(GlobalStreamId. ACKER-COMPONENT-ID ACKER-ACK-STREAM-ID)
(thrift/mk-direct-grouping))
(.put_to_inputs common
(GlobalStreamId. ACKER-COMPONENT-ID ACKER-FAIL-STREAM-ID)
(thrift/mk-direct-grouping))
))
(.put_to_bolts ret "__acker" acker-bolt)
))
根据是否配置"topology.acker.executors"获取acker线程的个数，如果没有配置num-executors绑定"topology.workers"的值，否则绑定"topology.acker.executors"的值。acker-bolt绑定生成的acker bolt对象。acker-inputs函数定义如下：
(let [bolt-ids (.. topology get_bolts keySet)
spout-ids (.. topology get_spouts keySet)
spout-inputs (apply merge
(for [id spout-ids]
{[id ACKER-INIT-STREAM-ID] ["id"]}
))
bolt-inputs (apply merge
(for [id bolt-ids]
{[id ACKER-ACK-STREAM-ID] ["id"]
[id ACKER-FAIL-STREAM-ID] ["id"]}
))]
(merge spout-inputs bolt-inputs)))
bolt-ids绑定topology所有bolt的id，spout-ids绑定所有spout的id，spout-inputs绑定来自spout的输入流，bolt-inputs绑定来自bolt的输入流，最后返回合并后的输入流(一个map对象)。ACKER-ACK-STREAM-ID和ACKER-FAIL-STREAM-ID表示acker的输出流。TOPOLOGY-TICK-TUPLE-FREQ-SECS表示tick tuple的频率，初始值为消息超时的时间。第一个dofor语句为每个bolt添加ACKER-ACK-STREAM-ID和ACKER-FAIL-STREAM-ID输出流用于将ack value发送个acker bolt，第二个dofor为每个spout设置了tick tuple的发送频率，并且设置了发送给acker bolt的ACKER-INIT-STREAM-ID输出流和来自ackerblot的两个输入流。这样acker bolt就可以与spout和bolt进行ack信息通信了。add-metric-components!函数主要功能就是将metric bolts添加到topology定义中。metric bolt主要用于统计线程executor相关的信息。add-metric-components!函数定义如下：
(doseq [[comp-id bolt-spec] (metrics-consumer-bolt-specs storm-conf topology)]
(.put_to_bolts topology comp-id bolt-spec)))
metrics-consumer-bolt-specs函数定义如下：
(defn metrics-consumer-bolt-specs [storm-conf topology]
(let [component-ids-that-emit-metrics (cons SYSTEM-COMPONENT-ID (keys (all-components topology)))
inputs (->> (for [comp-id component-ids-that-emit-metrics]
{[comp-id METRICS-STREAM-ID] :shuffle})
(into {}))
mk-bolt-spec (fn [class arg p]
(thrift/mk-bolt-spec*
inputs
(backtype.storm.metric.MetricsConsumerBolt. class arg)
{} :p p :conf {TOPOLOGY-TASKS p}))]
(map
(fn [component-id register]
[component-id (mk-bolt-spec (get register "class")
(get register "argument")
(or (get register "parallelism.hint") 1))])
(metrics-consumer-register-ids storm-conf)
(get storm-conf TOPOLOGY-METRICS-CONSUMER-REGISTER))))
component-ids-that-emit-metrics绑定包括system bolt在内的所有spout和bolt的id，inputs绑定了metric bolt的输入流，并且使用shuffle grouping。mk-bolt-spec绑定一个匿名函数，metrics-consumer-register-ids函数为每个metric consumer对象产生一个component id列表，get函数返回所有metric consumer对象，map函数返回component id和metric consumer对象集合的列表([component-id metric-consumer] [component-id metric-consumer]......)。add-system-components!函数主要功能是将system bolt添加到topology定义中。system bolt用于统计与进程worker相关的信息，如内存使用率，gc情况，网络吞吐量等。每个进程worker中只有一个system bolt。add-system-components!函数定义如下：
(let [system-bolt-spec (thrift/mk-bolt-spec*
{}
(SystemBolt.)
{SYSTEM-TICK-STREAM-ID (thrift/output-fields ["rate_secs"])
METRICS-TICK-STREAM-ID (thrift/output-fields ["interval"])}
:p 0
:conf {TOPOLOGY-TASKS 0})]
(.put_to_bolts topology SYSTEM-COMPONENT-ID system-bolt-spec)))
从thrift/mk-bolt-spec*函数的第一个参数{}我们可以发现system bolt没有输入流，从第三个参数可以发现它有两个输出流用于发送tick tuple，它的并行度为0，因为system bolt是与进程worker相关的，所以没有必要指定并行度。同时他也不需要执行任何task。add-metric-streams!函数主要功能用于给topology添加metric streams定义，add-metric-streams!定义如下：
(doseq [[_ component] (all-components topology)
:let [common (.get_common component)]]
(.put_to_streams common METRICS-STREAM-ID
(thrift/output-fields ["task-info" "data-points"]))))
给spout和bolt添加METRICS-STREAM-ID标示的metric stream。add-system-streams!函数与add-metric-streams!相似，给spout和bolt添加SYSTEM-STREAM-ID标示的system stream。submitTopologyWithOpts函数在调用system-topology!函数后，首先加锁，然后调用setup-storm-code函数，该函数的主要功能就是将上传给nimbus的jar包、topology和配置信息拷贝到{storm.local.dir}/nimbus/stormdist/{topology id}目录中，定义如下：
(let [stormroot (master-stormdist-root conf storm-id)]
(FileUtils/forceMkdir (File. stormroot))
(FileUtils/cleanDirectory (File. stormroot))
(setup-jar conf tmp-jar-location stormroot)
(FileUtils/writeByteArrayToFile (File. (master-stormcode-path stormroot)) (Utils/serialize topology))
(FileUtils/writeByteArrayToFile (File. (master-stormconf-path stormroot)) (Utils/serialize storm-conf))
))
setup-jar函数将{storm.local.dir}/nimbus/inbox/中的jar包拷贝到{storm.local.dir}/nimbus/stormdist/{topology id}目录，并重命名为stormjar.jar。FileUtils/writeByteArrayToFile将topology对象和storm-conf序列化后分别保存到stormcode.ser和stormconf.ser。setup-heartbeats!函数定义在cluster.clj文件中，是StormClusterState协议的一个函数，主要功能就是在zookeeper上创建该topology用于存放心跳信息的目录。心跳目录：
/storm/workerbeats/{topology id}/。
start-storm函数的主要功能读取整个集群的配置信息、nimbus的配置信息、从stormconf.ser反序列化topology配置信息和从stormcode.ser反序列化出topology，然后通过调用activate-storm!函数将topology的元数据StormBase对象写入zookeeper的/storm/storms/{topology id}文件中。定义如下：
{:pre [(#{:active :inactive} topology-initial-status)]}
(let [storm-cluster-state (:storm-cluster-state nimbus)
conf (:conf nimbus)
storm-conf (read-storm-conf conf storm-id)
topology (system-topology! storm-conf (read-storm-topology conf storm-id))
num-executors (->> (all-components topology) (map-val num-start-executors))]
(log-message "Activating " storm-name ": " storm-id)
(.activate-storm! storm-cluster-state
storm-id
(StormBase. storm-name
(current-time-secs)
{:type topology-initial-status}
(storm-conf TOPOLOGY-WORKERS)
num-executors))))
submitTopologyWithOpts函数最后调用mk-assignments函数进行任务分配。任务分配是stom架构的重要组成部分。鉴于篇幅问题，有关任务分配的源码分析会在之后的文章中讲解。