1 Recovery Tuning Main techniques Put the log on a dedicated disk Delay writing updates to the database disks as long as possible Setting proper intervals.

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Presentation transcript:

1 Recovery Tuning Main techniques Put the log on a dedicated disk Delay writing updates to the database disks as long as possible Setting proper intervals for DB dumping and checkpointing Reduce the size of large update transactions

2 Separate Disk for the Log DB2 UDB v7.1 on Windows % performance improvement if log is located on a different disk Controller cache hides negative impact mid-range server, with Adaptec RAID controller (80Mb RAM) and 2x18Gb disk drives. Figure 2.18 in the textbook shows a 30% improvement

3 Tuning Database Writes Database writes caused by transactions tend to be random Better to be delayed as much as possible Sufficient info in the log for recovery But eventually they need to be written to the disk To reduce recovery time When to write? Forced: when the buffer is full (or nearly full) Opportunistic: when no extra overhead for disk seeking Checkpoint: force all committed writes to disk

4 Writing Dirty Pages to the Disk When the number of dirty pages is greater than a given parameter (Oracle 8) When the number of dirty pages crosses a given threshold (less than 3% of free pages in the database buffer for SQL Server 7) When the log is full, a checkpoint is forced. This can have a significant impact on performance.

5 Tune Checkpoint Intervals Oracle 8i on Windows 2000 A checkpoint (partial flush of dirty pages to disk) occurs at regular intervals or when the log is full: Impacts the performance of on-line processing + Reduces the size of log + Reduces time to recover from a crash

6 Group Commit Log-writing a bottleneck if every committing transaction needs a write to the log Group commit Write the logs of multiple transactions in batch Need to use a “log buffer” (another thing to tune!) Better throughput if many concurrent short update transactions Longer response time for individual transactions This is a problem if they hold lock Early release of locks can cause problems, but the risk is remote

7 Log IO - Data Settings: lineitem ( L_ORDERKEY, L_PARTKEY, L_SUPPKEY, L_LINENUMBER, L_QUANTITY, L_EXTENDEDPRICE, L_DISCOUNT, L_TAX, L_RETURNFLAG, L_LINESTATUS, L_SHIPDATE, L_COMMITDATE, L_RECEIPTDATE, L_SHIPINSTRUCT, L_SHIPMODE, L_COMMENT ); READ COMMITTED isolation level Empty table Dual Xeon (550MHz,512Kb), 1Gb RAM, Internal RAID controller from Adaptec (80Mb), 4x18Gb drives (10000RPM), Windows 2000.

8 Log IO - Transactions No Concurrent Transactions: Insertions [ inserts, 10 threads], e.g., insert into lineitem values (1,7760,401,1,17, ,0.04,0.02,'N','O', ' ',' ',' ','DELIVER IN PERSON','TRUCK','blithely regular ideas caj');

9 Group Commits DB2 UDB v7.1 on Windows 2000 Log records of many transactions are written together Increases throughput by reducing the number of writes At cost of increased minimum response time.

10 Transaction Chopping Some transactions, in particular batch transactions, can be very long A lot of log information Very costly for recovery Solution Transaction chopping An easy to understand concept Formal work in appendix B of the textbook

11 Summary In this module, we have covered: The principles of recovery How to optimise recovery-related options Put the log on a dedicated disk Delay writing updates Using checkpoint and dump properly Reduce the size of update transactions

CS5226 Week 6 Operating System & Database Performance Tuning

13 Outline Part 1: Operating systems and DBMS Part 2: OS-related tuning

14 Operating System Operating system is an interface between hardware and other software, supporting: Processes and threads; Paging, buffering and IO scheduling Multi-tasking File system Other utilities such as timing, networking and performing monitoring hardware

15 Scheduling Process versus thread Scheduling based on time-slicing, IO, priority etc Different from transaction scheduling The cost of content switching When switch is desirable? And when is not? The administrator can set priorities to processes/threads Case 1: The DBMS runs at a lower priority Case 2: Different transactions run at different priority Case 3: Online transactions with higher priority than offline transactions

16 Priority Inversion Let priorities T1 > T2s > T3 T1 T2s T3 Lock x Request X … a solution: priority inheritance

17 Database Buffers Application buffers DBMS buffers OS buffers An application can have its own in- memory buffers (e.g., variables in the program; cursors); A logical read/write will be issued to the DBMS if the data needs to be read/written to the DBMS; A physical read/write is issued by the DBMS using its systematic page replacement algorithm. And such a request is passed to the OS. OS may initiate IO operations to support the virtual memory the DBMS buffer is built on.

18 Database Buffer Size Buffer too small, then hit ratio too small hit ratio = (logical acc. - physical acc.) / (logical acc.) Buffer too large, paging Recommended strategy: monitor hit ratio and increase buffer size until hit ratio flattens out. If there is still paging, then buy memory. LOGDATA RAM Paging Disk DATABASE PROCESSES DATABASE BUFFER

19 Buffer Size - Data Settings: employees(ssnum, name, lat, long, hundreds1, hundreds2); clustered index c on employees(lat); (unused) 10 distinct values of lat and long, 100 distinct values of hundreds1 and hundreds rows (630 Mb); Warm Buffer Dual Xeon (550MHz,512Kb), 1Gb RAM, Internal RAID controller from Adaptec (80Mb), 4x18Gb drives (10000 RPM), Windows 2000.

20 Buffer Size - Queries Queries: Scan Query select sum(long) from employees; Multipoint query select * from employees where lat = ?;

21 Database Buffer Size SQL Server 7 on Windows 2000 Scan query: LRU (least recently used) does badly when table spills to disk as Stonebraker observed 20 years ago. Multipoint query: Throughput increases with buffer size until all data is accessed from RAM.

22 Multiprogramming Levels More concurrent users Better utilization of CPU cycles (and other system resources) Risk of excessive page swapping More lock conflicts So how many exactly Depends on transaction profiles Experiments to find the best value And this parameter may change when application patterns change Feedback control mechanism

23 Disk Layout and Access Larger disk allocation chunks improves write performance At the cost of disk utilisation Setting disk usage factor Low when expecting updates/inserts Higher for scan-type of queries Prefetching within DBMS; not OS For non-random accesses

24 Scan Performance - Data Settings: lineitem ( L_ORDERKEY, L_PARTKEY, L_SUPPKEY, L_LINENUMBER, L_QUANTITY, L_EXTENDEDPRICE, L_DISCOUNT, L_TAX, L_RETURNFLAG, L_LINESTATUS, L_SHIPDATE, L_COMMITDATE, L_RECEIPTDATE, L_SHIPINSTRUCT, L_SHIPMODE, L_COMMENT ); rows Lineitem tuples are ~ 160 bytes long Cold Buffer Dual Xeon (550MHz,512Kb), 1Gb RAM, Internal RAID controller from Adaptec (80Mb), 4x18Gb drives (10000RPM), Windows 2000.

25 Scan Performance - Queries Queries: select avg(l_discount) from lineitem;

26 Usage Factor DB2 UDB v7.1 on Windows 2000 Usage factor is the percentage of the page used by tuples and auxiliary data structures (the rest is reserved for future) Scan throughput increases with usage factor.

27 Prefetching DB2 UDB v7.1 on Windows 2000 Throughput increases up to a certain point when prefetching size increases.

28 Summary In this module, we have covered: A review of OS from the DBMS perspective How to optimise OS-related parameters and options Thread Buffer, and File system