利用SemanticAnalyzerHook来过滤不加分区条件的Hive查询
我们Hadoop集群中将近百分之80的作业是通过Hive来提交的，由于Hive写起来简单便捷，而且我们又提供了Hive Web Client，所以使用范围很广，包括ba，pm，po，sales都在使用hive进行ad-hoc查询，但是hive在降低用户使用门槛的同时，也使得用户经常写不合理开销很大的语句，生成了很多的mapreduce job，占用了大量slot数，其中最典型的例子就是分区表查询，不指定分区条件，导致hive没有做partition pruner优化，进而读入了所有的表数据，占用大量IO和计算资源。 为了尽可能规避这种情况，我们可以利用了hive的hook机制，在hook中实现一些方法来对语句做预判，第一期先不会直接block住语句，而是记录有问题的语句来公告警示. 具体做法是实现HiveSemanticAnalyzerHook接口，preAnalyze方法和postAnalyze方法会分别在compile函数之前和之后执行，我们只要实现preAnalyze方法，遍历传进来的ASTNode抽象语法树，获取左子树的From表名和右子树的where判断条件key值，如果该From表是分区表的话，会通过metastore client获取它的所有分区key名字，用户指定的where条件中只要出现任何一个分区key，则此语句通过检测，否则会在标准错误中输出一条warning，并且在后台log中记录用户名和执行语句，每隔一段时间会将这些bad case在hive-user组邮箱进行公示，希望能通过这种方式来起到相互警示和学习的效果.
compile函数中根据hiveconf中指定的hive.semantic.analyzer.hook来反射实例化hook类，此处为实现AbstractSemanticAnalyzerHook的DPSemanticAnalyzerHook
package org.apache.hadoop.hive.ql.parse;import java.io.Serializable;import java.util.ArrayList;import java.util.List;import org.apache.commons.lang.StringUtils;import org.apache.hadoop.hive.metastore.api.FieldSchema;import org.apache.hadoop.hive.ql.exec.Task;import org.apache.hadoop.hive.ql.metadata.Hive;import org.apache.hadoop.hive.ql.metadata.HiveException;import org.apache.hadoop.hive.ql.metadata.Table;import org.apache.hadoop.hive.ql.session.SessionState;import org.apache.hadoop.hive.ql.session.SessionState.LogHelper;import org.apache.hadoop.hive.shims.ShimLoader;public class DPSemanticAnalyzerHook extends AbstractSemanticAnalyzerHook { private final static String NO_PARTITION_WARNING = "WARNING: HQL is not efficient, Please specify partition condition! HQL:%s ;USERNAME:%s"; private final SessionState ss = SessionState.get(); private final LogHelper console = SessionState.getConsole(); private Hive hive = null; private String username; private String currentDatabase = "default"; private String hql; private String whereHql; private String tableAlias; private String tableName; private String tableDatabaseName; private Boolean needCheckPartition = false; @Override public ASTNode preAnalyze(HiveSemanticAnalyzerHookContext context, ASTNode ast) throws SemanticException { try { hql = ss.getCmd().toLowerCase(); hql = StringUtils.replaceChars(hql, '\n', ' '); if (hql.contains("where")) { whereHql = hql.substring(hql.indexOf("where")); } username = ShimLoader.getHadoopShims().getUserName(context.getConf()); if (ast.getToken().getType() == HiveParser.TOK_QUERY) { try { hive = context.getHive(); currentDatabase = hive.getCurrentDatabase(); } catch (HiveException e) { throw new SemanticException(e); } extractFromClause((ASTNode) ast.getChild(0)); if (needCheckPartition && !StringUtils.isBlank(tableName)) { String dbname = StringUtils.isEmpty(tableDatabaseName) ? currentDatabase : tableDatabaseName; String tbname = tableName; String[] parts = tableName.split("."); if (parts.length == 2) { dbname = parts[0]; tbname = parts[1]; } Table t = hive.getTable(dbname, tbname); if (t.isPartitioned()) { if (StringUtils.isBlank(whereHql)) { console.printError(String.format(NO_PARTITION_WARNING, hql, username)); } else { List<FieldSchema> partitionKeys = t.getPartitionKeys(); List<String> partitionNames = new ArrayList<String>(); for (int i = 0; i < partitionKeys.size(); i++) { partitionNames.add(partitionKeys.get(i).getName().toLowerCase()); } if (!containsPartCond(partitionNames, whereHql, tableAlias)) { console.printError(String.format(NO_PARTITION_WARNING, hql, username)); } } } } } } catch (Exception ex) { ex.printStackTrace(); } return ast; } private boolean containsPartCond(List<String> partitionKeys, String sql, String alias) { for (String pk : partitionKeys) { if (sql.contains(pk)) { return true; } if (!StringUtils.isEmpty(alias) && sql.contains(alias + "." + pk)) { return true; } } return false; } private void extractFromClause(ASTNode ast) { if (HiveParser.TOK_FROM == ast.getToken().getType()) { ASTNode refNode = (ASTNode) ast.getChild(0); if (refNode.getToken().getType() == HiveParser.TOK_TABREF && ast.getChildCount() == 1) { ASTNode tabNameNode = (ASTNode) (refNode.getChild(0)); int refNodeChildCount = refNode.getChildCount(); if (tabNameNode.getToken().getType() == HiveParser.TOK_TABNAME) { if (tabNameNode.getChildCount() == 2) { tableDatabaseName = tabNameNode.getChild(0).getText().toLowerCase(); tableName = BaseSemanticAnalyzer.getUnescapedName((ASTNode) tabNameNode.getChild(1)) .toLowerCase(); } else if (tabNameNode.getChildCount() == 1) { tableName = BaseSemanticAnalyzer.getUnescapedName((ASTNode) tabNameNode.getChild(0)) .toLowerCase(); } else { return; } if (refNodeChildCount == 2) { tableAlias = BaseSemanticAnalyzer.unescapeIdentifier(refNode.getChild(1).getText()) .toLowerCase(); } needCheckPartition = true; } } } } @Override public void postAnalyze(HiveSemanticAnalyzerHookContext context, List<Task<? extends Serializable>> rootTasks) throws SemanticException { // LogHelper console = SessionState.getConsole(); // Set<ReadEntity> readEntitys = context.getInputs(); // console.printInfo("Total Read Entity Size:" + readEntitys.size()); // for (ReadEntity readEntity : readEntitys) { // Partition p = readEntity.getPartition(); // Table t = readEntity.getTable(); // } }}