Logs are ubiquitous for system monitoring and debugging. However, there lacks a comprehensive system that is capable of performing heterogeneous log organization and analysis for various purposes with very limited domain knowledge and human surveillance. In this manuscript, a novel system for heterogeneous log analysis is proposed. The system, denoted as Heterogeneous Log Analyzer (HLAer), achieves the following goals concurrently: 1) heterogeneous log categorization and organization; 2) automatic log format recognition and 3) heterogeneous log indexing. Meanwhile, HLAer supports queries and outlier detection on heterogeneous logs. HLAer provides a framework which is purely dataoriented and thus general enough to adapt to arbitrary log formats, applications or systems. The current implementation of HLAer is scalable to Big Data.