Flink源码分析系列文档目录
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前言
本篇分析下Flink安全认证部分的处理方式。主要为Kerberos认证相关内容。下面从配置项开始分析。
SecurityConfiguration
此类包含了Flink安全认证相关的配置项。它们的含义如下:
zookeeper.sasl.disable:是否启用Zookeeper SASL。
security.kerberos.login.keytab:Kerberos认证keytab文件的路径。
security.kerberos.login.principal:Kerberos认证principal。
security.kerberos.login.use-ticket-cache:Kerberos认证是否使用票据缓存。
security.kerberos.login.contexts:Kerberos登录上下文名称,等效于JAAS文件的entry name。
zookeeper.sasl.service-name:Zookeeper SASL服务名。默认为zookeeper
。
zookeeper.sasl.login-context-name:Zookeeper SASL登陆上下文名称。默认为Client
。
security.context.factory.classes:包含哪些 SecurityContextFactory
。默认值为:
- org.apache.flink.runtime.security.contexts.HadoopSecurityContextFactory
- org.apache.flink.runtime.security.contexts.NoOpSecurityContextFactory
security.module.factory.classes:包含哪些SecurityModuleFactory
。 默认值为:
- org.apache.flink.runtime.security.modules.HadoopModuleFactory
- org.apache.flink.runtime.security.modules.JaasModuleFactory
- org.apache.flink.runtime.security.modules.ZookeeperModuleFactory
SecurityUtils
SecurityUtils.install
方法是提交Flink任务安全认证的入口方法,用于安装安全配置。它的代码如下所示:
public static void install(SecurityConfiguration config) throws Exception {
// Install the security modules first before installing the security context
// 安装安全模块
installModules(config);
// 安装安全上下文
installContext(config);
}
installModules
方法用于安装安全认证模块。安全认证模块的内容在后面分析。
static void installModules(SecurityConfiguration config) throws Exception {
// install the security module factories
List modules = new ArrayList<>();
// 遍历所有SecurityModuleFactory的配置
for (String moduleFactoryClass : config.getSecurityModuleFactories()) {
SecurityModuleFactory moduleFactory = null;
try {
// 使用ServiceLoader加载ModuleFactory
moduleFactory = SecurityFactoryServiceLoader.findModuleFactory(moduleFactoryClass);
} catch (NoMatchSecurityFactoryException ne) {
LOG.error("Unable to instantiate security module factory {}", moduleFactoryClass);
throw new IllegalArgumentException("Unable to find module factory class", ne);
}
// 使用factory创建出SecurityModule
SecurityModule module = moduleFactory.createModule(config);
// can be null if a SecurityModule is not supported in the current environment
// 安装module
// 添加module到modules集合
if (module != null) {
module.install();
modules.add(module);
}
}
installedModules = modules;
}
installContext
方法用于安装安全上下文环境,它的用途同样在后面章节介绍。
static void installContext(SecurityConfiguration config) throws Exception {
// install the security context factory
// 遍历SecurityContextFactories
// 配置项名称为security.context.factory.classes
for (String contextFactoryClass : config.getSecurityContextFactories()) {
try {
// 使用ServiceLoader,加载SecurityContextFactory
SecurityContextFactory contextFactory =
SecurityFactoryServiceLoader.findContextFactory(contextFactoryClass);
// 检查SecurityContextFactory是否和配置文件兼容(1)
if (contextFactory.isCompatibleWith(config)) {
try {
// 创建出第一个兼容的SecurityContext
installedContext = contextFactory.createContext(config);
// install the first context that's compatible and ignore the remaining.
break;
} catch (SecurityContextInitializeException e) {
LOG.error(
"Cannot instantiate security context with: " + contextFactoryClass,
e);
} catch (LinkageError le) {
LOG.error(
"Error occur when instantiate security context with: "
+ contextFactoryClass,
le);
}
} else {
LOG.debug("Unable to install security context factory {}", contextFactoryClass);
}
} catch (NoMatchSecurityFactoryException ne) {
LOG.warn("Unable to instantiate security context factory {}", contextFactoryClass);
}
}
if (installedContext == null) {
LOG.error("Unable to install a valid security context factory!");
throw new Exception("Unable to install a valid security context factory!");
}
}
数字标注内容解析:
- 这里分析下
isCompatibleWith
方法逻辑,SecurityContextFactory
具有HadoopSecurityContextFactory
和NoOpSecurityContextFactory
两个实现类。其中HadoopSecurityContextFactory
要求security.module.factory.classes
配置项包含org.apache.flink.runtime.security.modules.HadoopModuleFactory
,并且要求org.apache.hadoop.security.UserGroupInformation
在classpath中。NoOpSecurityContextFactory
无任何要求。
SecurityModule
SecurityModule
分别为不同类型服务提供安全认证功能,包含3个子类:
- HadoopModule:使用
UserGroupInformation
方式认证。 - JaasModule:负责安装JAAS配置,在进程范围内生效。
- ZookeeperModule:提供Zookeeper安全配置。
HadoopModule
HadoopModule
包含了Flink的SecurityConfiguration
和Hadoop的配置信息(从Hadoop配置文件读取,读取逻辑在HadoopUtils.getHadoopConfiguration
,后面分析)。
install方法
install
方法使用Hadoop提供的UserGroupInformation
进行认证操作。
@Override
public void install() throws SecurityInstallException {
// UGI设置hadoop conf
UserGroupInformation.setConfiguration(hadoopConfiguration);
UserGroupInformation loginUser;
try {
// 如果Hadoop启用了安全配置
if (UserGroupInformation.isSecurityEnabled()
&& !StringUtils.isBlank(securityConfig.getKeytab())
&& !StringUtils.isBlank(securityConfig.getPrincipal())) {
// 获取keytab路径
String keytabPath = (new File(securityConfig.getKeytab())).getAbsolutePath();
// 使用UGI认证Flink conf中配置的keytab和principal
UserGroupInformation.loginUserFromKeytab(securityConfig.getPrincipal(), keytabPath);
// 获取认证的用户
loginUser = UserGroupInformation.getLoginUser();
// supplement with any available tokens
// 从HADOOP_TOKEN_FILE_LOCATION读取token缓存文件
String fileLocation =
System.getenv(UserGroupInformation.HADOOP_TOKEN_FILE_LOCATION);
// 如果有本地token缓存
if (fileLocation != null) {
Credentials credentialsFromTokenStorageFile =
Credentials.readTokenStorageFile(
new File(fileLocation), hadoopConfiguration);
// if UGI uses Kerberos keytabs for login, do not load HDFS delegation token
// since
// the UGI would prefer the delegation token instead, which eventually expires
// and does not fallback to using Kerberos tickets
// 如果UGI使用keytab方式登录,不用加载HDFS的delegation token
// 因为UGI倾向于使用delegation token,这些token最终会失效,不会使用kerberos票据
Credentials credentialsToBeAdded = new Credentials();
final Text hdfsDelegationTokenKind = new Text("HDFS_DELEGATION_TOKEN");
Collection> usrTok =
credentialsFromTokenStorageFile.getAllTokens();
// If UGI use keytab for login, do not load HDFS delegation token.
// 遍历token存储文件中的token
// 将所有的非delegation token添加到凭据中
for (Token token : usrTok) {
if (!token.getKind().equals(hdfsDelegationTokenKind)) {
final Text id = new Text(token.getIdentifier());
credentialsToBeAdded.addToken(id, token);
}
}
// 为loginUser添加凭据
loginUser.addCredentials(credentialsToBeAdded);
}
} else {
// 如果没有启动安全配置
// 从当前用户凭据认证
// login with current user credentials (e.g. ticket cache, OS login)
// note that the stored tokens are read automatically
try {
// Use reflection API to get the login user object
// 反射调用如下方法
// UserGroupInformation.loginUserFromSubject(null);
Method loginUserFromSubjectMethod =
UserGroupInformation.class.getMethod(
"loginUserFromSubject", Subject.class);
loginUserFromSubjectMethod.invoke(null, (Subject) null);
} catch (NoSuchMethodException e) {
LOG.warn("Could not find method implementations in the shaded jar.", e);
} catch (InvocationTargetException e) {
throw e.getTargetException();
}
// 获取当前登录用户
loginUser = UserGroupInformation.getLoginUser();
}
LOG.info("Hadoop user set to {}", loginUser);
if (HadoopUtils.isKerberosSecurityEnabled(loginUser)) {
boolean isCredentialsConfigured =
HadoopUtils.areKerberosCredentialsValid(
loginUser, securityConfig.useTicketCache());
LOG.info(
"Kerberos security is enabled and credentials are {}.",
isCredentialsConfigured ? "valid" : "invalid");
}
} catch (Throwable ex) {
throw new SecurityInstallException("Unable to set the Hadoop login user", ex);
}
}
HadoopUtils.getHadoopConfiguration 方法
这个方法为读取Hadoop配置文件的逻辑,较为复杂,接下来详细分析下。
public static Configuration getHadoopConfiguration(
org.apache.flink.configuration.Configuration flinkConfiguration) {
// Instantiate an HdfsConfiguration to load the hdfs-site.xml and hdfs-default.xml
// from the classpath
// 创建个空的conf
Configuration result = new HdfsConfiguration();
// 标记是否找到hadoop配置文件
boolean foundHadoopConfiguration = false;
// We need to load both core-site.xml and hdfs-site.xml to determine the default fs path and
// the hdfs configuration.
// The properties of a newly added resource will override the ones in previous resources, so
// a configuration
// file with higher priority should be added later.
// Approach 1: HADOOP_HOME environment variables
// 保存两个可能的hadoop conf路径
String[] possibleHadoopConfPaths = new String[2];
// 获取HADOOP_HOME环境变量的值
final String hadoopHome = System.getenv("HADOOP_HOME");
if (hadoopHome != null) {
LOG.debug("Searching Hadoop configuration files in HADOOP_HOME: {}", hadoopHome);
// 如果发现HADOOP_HOME环境变量的值
// 尝试分别从如下路径获取:
// $HADOOP_HOME/conf
// $HADOOP_HOME/etc/hadoop
possibleHadoopConfPaths[0] = hadoopHome + "/conf";
possibleHadoopConfPaths[1] = hadoopHome + "/etc/hadoop"; // hadoop 2.2
}
for (String possibleHadoopConfPath : possibleHadoopConfPaths) {
if (possibleHadoopConfPath != null) {
// 依次尝试读取possibleHadoopConfPath下的core-site.xml文件和hdfs-site.xml文件到hadoop conf中
foundHadoopConfiguration = addHadoopConfIfFound(result, possibleHadoopConfPath);
}
}
// Approach 2: Flink configuration (deprecated)
// 获取Flink配置项 fs.hdfs.hdfsdefault 对应的配置文件,加入hadoop conf
final String hdfsDefaultPath =
flinkConfiguration.getString(ConfigConstants.HDFS_DEFAULT_CONFIG, null);
if (hdfsDefaultPath != null) {
result.addResource(new org.apache.hadoop.fs.Path(hdfsDefaultPath));
LOG.debug(
"Using hdfs-default configuration-file path from Flink config: {}",
hdfsDefaultPath);
foundHadoopConfiguration = true;
}
// 获取Flink配置项 fs.hdfs.hadoopconf 对应的配置文件,加入hadoop conf
final String hdfsSitePath =
flinkConfiguration.getString(ConfigConstants.HDFS_SITE_CONFIG, null);
if (hdfsSitePath != null) {
result.addResource(new org.apache.hadoop.fs.Path(hdfsSitePath));
LOG.debug(
"Using hdfs-site configuration-file path from Flink config: {}", hdfsSitePath);
foundHadoopConfiguration = true;
}
// 获取Flink配置项 fs.hdfs.hadoopconf 对应的配置文件,加入hadoop conf
final String hadoopConfigPath =
flinkConfiguration.getString(ConfigConstants.PATH_HADOOP_CONFIG, null);
if (hadoopConfigPath != null) {
LOG.debug("Searching Hadoop configuration files in Flink config: {}", hadoopConfigPath);
foundHadoopConfiguration =
addHadoopConfIfFound(result, hadoopConfigPath) || foundHadoopConfiguration;
}
// Approach 3: HADOOP_CONF_DIR environment variable
// 从系统环境变量HADOOP_CONF_DIR目录中读取hadoop配置文件
String hadoopConfDir = System.getenv("HADOOP_CONF_DIR");
if (hadoopConfDir != null) {
LOG.debug("Searching Hadoop configuration files in HADOOP_CONF_DIR: {}", hadoopConfDir);
foundHadoopConfiguration =
addHadoopConfIfFound(result, hadoopConfDir) || foundHadoopConfiguration;
}
// Approach 4: Flink configuration
// add all configuration key with prefix 'flink.hadoop.' in flink conf to hadoop conf
// 读取Flink配置文件中所有以flink.hadoop.为前缀的key
// 将这些key截掉这个前缀作为新的key,和原先的value一起作为hadoop conf的配置项,存放入hadoop conf
for (String key : flinkConfiguration.keySet()) {
for (String prefix : FLINK_CONFIG_PREFIXES) {
if (key.startsWith(prefix)) {
String newKey = key.substring(prefix.length());
String value = flinkConfiguration.getString(key, null);
result.set(newKey, value);
LOG.debug(
"Adding Flink config entry for {} as {}={} to Hadoop config",
key,
newKey,
value);
foundHadoopConfiguration = true;
}
}
}
// 如果以上途径均未找到hadoop conf,显示告警信息
if (!foundHadoopConfiguration) {
LOG.warn(
"Could not find Hadoop configuration via any of the supported methods "
+ "(Flink configuration, environment variables).");
}
return result;
}
我们总结下Flink读取Hadoop配置文件的完整逻辑,从上到下为读取顺序:
- 读取
HADOOP_HOME
环境变量,如果存在,分别从它的conf
和etc/hadoop
目录下读取core-site.xml
和hdfs-site.xml
文件。 - 从Flink配置文件的
fs.hdfs.hdfsdefault
配置项所在目录下寻找。 - 从Flink配置文件的
fs.hdfs.hadoopconf
配置项所在目录下寻找。 - 从
HADOOP_CONF_DIR
环境变量对应的目录下寻找。 - 读取Flink配置文件中所有以
flink.hadoop.
为前缀的key,将这些key截掉这个前缀作为新的key,和原先的value一起作为hadoop conf的配置项,存放入hadoop conf。
JaasModule
install
方法读取了java.security.auth.login.config
系统变量对应的jaas配置,并且将Flink配置文件中相关配置转换为JAAS中的entry,合并到系统变量对应的jaas配置中并设置给JVM。代码如下所示:
@Override
public void install() {
// ensure that a config file is always defined, for compatibility with
// ZK and Kafka which check for the system property and existence of the file
// 读取java.security.auth.login.config系统变量值,用于在卸载module的时候恢复
priorConfigFile = System.getProperty(JAVA_SECURITY_AUTH_LOGIN_CONFIG, null);
// 如果没有配置
if (priorConfigFile == null) {
// Flink的 io.tmp.dirs配置项第一个目录为workingDir
// 将默认的flink-jaas.conf文件写入这个位置,创建临时文件,名为jass-xxx.conf
// 在JVM进程关闭的时候删除这个临时文件
File configFile = generateDefaultConfigFile(workingDir);
// 配置java.security.auth.login.config系统变量值
// 保证这个系统变量的值始终存在,这是为了兼容Zookeeper和Kafka
// 他们会去检查这个jaas文件是否存在
System.setProperty(JAVA_SECURITY_AUTH_LOGIN_CONFIG, configFile.getAbsolutePath());
LOG.info("Jaas file will be created as {}.", configFile);
}
// read the JAAS configuration file
// 读取已安装的jaas配置文件
priorConfig = javax.security.auth.login.Configuration.getConfiguration();
// construct a dynamic JAAS configuration
// 包装为DynamicConfiguration,这个配置是可以修改的
currentConfig = new DynamicConfiguration(priorConfig);
// wire up the configured JAAS login contexts to use the krb5 entries
// 从Flink配置文件中读取kerberos配置
// AppConfigurationEntry为Java读取Jaas配置文件中一段配置项的封装
// 一段配置项指的是大括号之内的配置
AppConfigurationEntry[] krb5Entries = getAppConfigurationEntries(securityConfig);
if (krb5Entries != null) {
// 遍历Flink配置项security.kerberos.login.contexts,作为entry name使用
for (String app : securityConfig.getLoginContextNames()) {
// 将krb5Entries对应的AppConfigurationEntry添加入currrentConfig
// 使用security.kerberos.login.contexts对应的entry name
currentConfig.addAppConfigurationEntry(app, krb5Entries);
}
}
// 设置新的currentConfig
javax.security.auth.login.Configuration.setConfiguration(currentConfig);
}
上面代码中getAppConfigurationEntries
方法逻辑较为复杂,下面给出它的解析。
getAppConfigurationEntries
方法从Flink的securityConfig
中读取配置,转换为JAAS entry的格式,存入AppConfigurationEntry
。如果Flink配置了security.kerberos.login.use-ticket-cache
,加载类似如下内容的文件,生成一个AppConfigurationEntry
叫做userKerberosAce
:
EntryName {
com.sun.security.auth.module.Krb5LoginModule optional
doNotPrompt=true
useTicketCache=true
renewTGT=true;
};
如果Flink中配置了security.kerberos.login.keytab
,会加载如下配置,生成一个AppConfigurationEntry
叫做keytabKerberosAce
:
EntryName {
com.sun.security.auth.module.Krb5LoginModule required
keyTab=keytab路径
doNotPrompt=true
useKeyTab=true
storeKey=true
principal=principal名称
refreshKrb5Config=true;
};
getAppConfigurationEntries
最后返回这两个AppConfigurationEntry
的集合,如果某一个为null,只返回其中一个。
ZookeeperModule
install
方法,主要作用为根据Flink配置,设置Zookeeper相关的几个系统变量的值。
@Override
public void install() throws SecurityInstallException {
// 获取zookeeper.sasl.client系统变量值,用于在卸载module的时候恢复
priorSaslEnable = System.getProperty(ZK_ENABLE_CLIENT_SASL, null);
// 读取Flink配置项zookeeper.sasl.disable的值,根据其语义(取反)设置为zookeeper.sasl.client系统变量
System.setProperty(
ZK_ENABLE_CLIENT_SASL, String.valueOf(!securityConfig.isZkSaslDisable()));
// 获取zookeeper.sasl.client.username系统变量值,用于在卸载module的时候恢复
priorServiceName = System.getProperty(ZK_SASL_CLIENT_USERNAME, null);
// 读取Flink配置项zookeeper.sasl.service-name
// 如果不为默认值zookeeper,设置zookeeper.sasl.client.username系统变量
if (!"zookeeper".equals(securityConfig.getZooKeeperServiceName())) {
System.setProperty(ZK_SASL_CLIENT_USERNAME, securityConfig.getZooKeeperServiceName());
}
// 获取zookeeper.sasl.clientconfig系统变量值,用于在卸载module的时候恢复
priorLoginContextName = System.getProperty(ZK_LOGIN_CONTEXT_NAME, null);
// 读取Flink配置项zookeeper.sasl.login-context-name
// 如果不为默认值Client,设置zookeeper.sasl.clientconfig系统变量
if (!"Client".equals(securityConfig.getZooKeeperLoginContextName())) {
System.setProperty(
ZK_LOGIN_CONTEXT_NAME, securityConfig.getZooKeeperLoginContextName());
}
}
SecurityContext
顾名思义为安全环境上下文,用于在不同认证环境下执行需要授权才能调用的逻辑。
HadoopSecurityContext
HadoopSecurityContext
用于在认证过的UserGroupInformation
中执行逻辑(封装在Callable
中)。
public class HadoopSecurityContext implements SecurityContext {
private final UserGroupInformation ugi;
public HadoopSecurityContext(UserGroupInformation ugi) {
this.ugi = Preconditions.checkNotNull(ugi, "UGI passed cannot be null");
}
public T runSecured(final Callable securedCallable) throws Exception {
return ugi.doAs((PrivilegedExceptionAction) securedCallable::call);
}
}
NoOpSecurityContext
NoOpSecurityContext
不做任何认证,直接运行Callable
。
public class NoOpSecurityContext implements SecurityContext {
@Override
public T runSecured(Callable securedCallable) throws Exception {
return securedCallable.call();
}
}
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