OSEE/ReqAndDesign

Logging

Requirements

• shall handle creation/update of thousands of log entries per second
• shall support logging by OSEE and other applications
• log entries related to an individual instance of a user request shall be able to be logically grouped and accessed
• log entries shall be quickly accessible based on any combination of source, user, timestamp, log type, duration, status
• log entries shall be accessible (especially) when an application server is unresponsive
• log entries shall be available until they are deleted by an admin or admin policy (applied by server automatically)
• at run-time logging shall be enabled/disabled based on any combination of user, source, log level, and type

Design

DB: entry_id, parent_id, timestamp, user_id, log_level, type_id, duration, status, details (maybe in JSON format) Java: Level level, long entryId, long timestamp, long duration, long userId, long typeId, long status, long parentId, String message

• id - random long returned for log method call
• parent_id - id of entry used for grouping this and related entries. Is negative for root entries and is the id of source of the entry client or server random id. Ranges are used to group by client/server kind (IDE client, app server, rest client).
• timestamp - long with ms since epoch
• user_id - long user id (artifact id of a user artifact)
• log_level - as defined by java.util.logging.Level
• type_id - a fine-grained application defined type (might use ranges) defined as tokens with a long and name (which is not in db)
• duration - starts at -1 and is never updated if duration does not apply, otherwise updates when the associated job ends with duration in ms
• Status:

 0     initial value
 1-99  percent complete
 100   completed normally
 101   completed abnormally

• high performance
  • option A - 2 identical length arraylists are allocated with an initial configurable size
  • log entries are added to a queue see data structure options
  • a queue to collect log entries for a short time (configurable) and then inserts them in batch. This means that any update to a log entry that occurs in less than this configured time will not require a database update (i.e. writing the duration of a short operation). This also means only one thread writes to the log table per server.
  • Optimize JDBC Performance

long create[Level](long userId, long typeId);

long create[Level](long userId, long typeId, long parentId);

long create[Level](long userId, long typeId, String format, Object... args);

long create[Level](long userId, long typeId, long parentId, String format, Object... args);

void updateEntry(long entryId, long status, String format, Object... args);

void updateEntry(long entryId, long status);

RuntimeException create[Level](long userId, long typeId, Throwable throwable);

RuntimeException create[Level](long userId, long typeId, long parentId, Throwable throwable);

RuntimeException updateEntry(long entryId, Throwable throwable);

Exception Handling

Requirements

• avoid unnecessary wrapping of exceptions

Design

Checked exceptions I love you, but you have to go Why should you use Unchecked exceptions over Checked exceptions Clean Code by Example: Checked versus unchecked exceptions

• Use application specific exceptions that extend RuntimeException - application specific allows for setting exception breakpoints in the debugger
• Do not declare any run-time exceptions in any method signatures