Rethinking Serializable Multi-version Concurrency Control. Jose Faleiro and Daniel Abadi Yale University

Transcription

1 Rethinking Serializable Multi-version Concurrency Control Jose Faleiro and Daniel Abadi Yale University

2 Theory: Single- vs Multi-version Systems Single-version system T r Read X X 0 T w Write X Multi-version system T r Read X X 0 T w Write X

3 Theory: Single- vs Multi-version Systems Single-version system T r Read X X 0 T w Write X T r and T w cannot simultaneously execute Multi-version system T r Read X T w Write X X 0

4 Theory: Single- vs Multi-version Systems Single-version system T r Read X X 0 T w Write X T r and T w cannot simultaneously execute Multi-version system T r Read X X 0 T w Write X X 1 T r and T w can both simultaneously make progress

5 Theory: Single- vs Multi-version Systems Single-version system T r Read X X 0 T w Write X T r and T w cannot simultaneously execute Multi-versioning obviously buys more concurrency, right? Multi-version system T r Read X X 0 T w Write X X 1 T r and T w can both simultaneously make progress

6 Practice: Multi-version Systems T 0 : if savings + checking >= 100 savings -= 100 T 1 : if savings + checking >= 75 checking -= 75 Savings: 100 Checking: 50 Constraint: savings + checking >= 0

7 Practice: Multi-version Systems T 0 commits T 0 : if savings + checking >= 100 savings -= 100 T 1 : if savings + checking >= 75 checking -= 75 Savings: 100 Savings: 0 Checking: 50 Constraint: savings + checking >= 0

8 Practice: Multi-version Systems T 0 commits T 0 : if savings + checking >= 100 savings -= 100 T 1 commits T 1 : if savings + checking >= 75 checking -= 75 Savings: 100 Savings: 0 Checking: 50 Checking: -25 Constraint: savings + checking >= 0

9 Practice: Multi-version Systems T 0 commits T 0 : if savings + checking >= 100 savings -= 100 T 1 commits T 1 : if savings + checking >= 75 checking -= 75 Savings: 100 Savings: 0 Checking: 50 Checking: -25 Constraint: savings + checking >= 0

10 Practice: Multi-version Systems T 0 commits T 0 : if savings + checking >= 100 savings -= 100 T 1 commits T 1 : if savings + checking >= 75 checking -= 75 Solution : Use conservative isolation techniques similar to Savings: 100 single-version Savings: systems 0 Checking: 50 Checking: -25 Constraint: savings + checking >= 0

11 Practice: Multi-version Systems T 0 : savings += 100 Monotonic timestamp generator begin: end: Savings: 25 Savings: 75 begin: 0 end: 10 begin: 10 end: inf

12 Practice: Multi-version Systems T 0 : savings += 100 Monotonic timestamp generator begin: end: Savings: 25 Savings: 75 begin: 0 end: 10 begin: 10 end: inf

13 Practice: Multi-version Systems T 0 : savings += 100 Monotonic timestamp generator begin: 12 end: Savings: 25 begin: 0 end: 10 begin: 10 Savings: 75 end: inf Determines snapshot visible to txn

14 Practice: Multi-version Systems T 0 : savings += 100 Monotonic timestamp generator begin: 12 end: Savings: 25 Savings: 75 begin: 0 end: 10 begin: 10 end: inf

15 Practice: Multi-version Systems T 0 : savings += 100 begin: 12 end: 18 Determines visibility of txn s writes Monotonic timestamp generator Savings: 25 Savings: 75 Savings: 175 begin: 0 end: 10 begin: 10 end: 18 begin: 18 end: inf

16 Practice: Multi-version Systems T 0 : savings += 100 Monotonic timestamp generator begin: 12 end: 18 Global counter Scalability Savings: 25 bottleneck! Savings: 75 Savings: 175 begin: 0 end: 10 begin: 10 end: 18 begin: 18 end: inf

17 Practice: Multi-version Systems T 0 : Version management savings += 100 overhead Monotonic timestamp generator begin: 12 end: 18 Savings: 25 Savings: 75 Savings: 175 begin: 0 end: 10 begin: 10 end: 18 begin: 18 end: inf

18 Practice: Multi-version Systems Offer the same amount of concurrency as singleversion systems Do not effectively exploit multi-versioning Significant sources of overhead Contended counters Version management

19 Practice: Multi-version Systems Offer the same amount of concurrency as singleversion systems Do not effectively exploit multi-versioning Significant sources of overhead Contended counters Version management Fundamental issue with concurrency control protocols Severe performance degradation on multi-core main-memory systems

20 Root Cause Multi-version databases enforce serial order dynamically Concurrency control occurs during transaction execution Requires conservative concurrency control Same read-write concurrency as single-versioning Concurrency control meta-data prone to contention

21 Our Approach: Bohm Separate concurrency control from transaction execution Concurrency control determines transaction order and version visibility Execution performs logic given concurrency control ordering

22 Bohm Overview T 0 T 0 T 1 Concurrency Control T 1 T 2 Execution T 2 T 3 T 3 T 4 Determine legal schedule T 4 Perform logic

23 Extra Requirements Transactions entire logic must be submitted in one piece Transactions write-sets must be deducible prior to their execution

24 Concurrency Control Layer Take a totally ordered batch of txns as input Create a new version for each write Versions created in sequence order

25 Concurrency Control Layer Partition data across multiple threads T 200 a b h f a e g CC0 b c h CC 1 d f i CC 2

26 Concurrency Control Layer Partition data across multiple threads For every write, create a new version T 200 a b h f a e g CC0 b c h CC 1 d f i CC 2

27 Concurrency Control Layer Partition data across multiple threads For every write, create a new version a e g begin: 0 value 0 end: inf T 200 a b h f a e g CC0 b c h CC 1 d f i CC 2

28 Concurrency Control Layer Partition data across multiple threads For every write, create a new version T 200 a b h f a e g T 200 a b h f begin: 200 end: inf prev value 0 a e g b c h d f i begin: 0 end: 200 CC0 CC 1 CC 2

29 Concurrency Control Layer Partition data across multiple threads For every write, create a new version a e g T 200 a b h f begin: 200 end: inf a e g CC0 T 200 Version contains txn a b h f reference b c h CC 1 d f i No value yet CC 2 value 0 prev begin: 0 end: 200

30 Execution Layer Begins executing a batch after concurrency control completes Perform txn logic, write out data a e g T 200 a b h f begin: 200 end: inf prev value 0 begin: 0 end: 200

31 Execution Layer Begins executing a batch after concurrency control completes Perform txn logic, write out data a e g T 200 a b h f begin: 200 end: inf prev Replace txn reference with actual data value 0 begin: 0 end: 200

32 Execution Layer Begins executing a batch after concurrency control completes Perform txn logic, write out data a e g value 1 begin: 200 end: inf prev Replace txn reference with actual data value 0 begin: 0 end: 200

33 Implications of Design Concurrency control fixes txn snapshots prior to their execution a e g T 200 a b h f begin: 200 end: inf prev Execution only produces values No logical locking/validation value 0 begin: 0 end: 200

34 What have we gained? Strong concurrency guarantees Reads never block writes Write-write conflicts never lead to aborts Significant reduction in contention No contended counters Contention-free concurrency control

35 Baselines Hekaton State-of-the-art MVCC protocol No garbage collection, simple array indices Snapshot Isolation Not serializable Based on Hekaton OCC Silo Decentralized timestamps, latch-free validation Two-Phase Locking No global latches, deadlock free

36 Evaluation Effect of read-write concurrency YCSB-like: 2RMWs + 8 Reads High contention

37 Read-Write Concurrency Throughput (txns/sec) 2.0 M 1.5 M 1.0 M 0.5 M Bohm SI Hekaton 2PL OCC 2x 0.0 M Number of Threads

38 Conclusions State-of-the-art databases are unable to reduce read-write conflicts despite using multi-versioning Bohm: Separate concurrency control from execution Bohm makes strong concurrency guarantees Reads never block writes Write-write conflicts never lead to aborts Bohm eliminates contention due to concurrency control

39 Thanks! JMFALEIRO.COM

40 Limitations of Contended Counters Throughput (txns/sec) 4.0 M 3.5 M 3.0 M 2.5 M 2.0 M 1.5 M 1.0 M Bohm 2PL OCC SI Hekaton 3x 0.5 M 0.0 M Number of Threads

41 Varying Contention Throughput (txns/sec) 3.0 M 2.5 M 2.0 M 1.5 M 1.0 M 0.5 M 0.0 M Increasing contention OCC Bohm 2PL SI Hekaton Theta

42 Long Running Read-only Txns Throughput (txns/sec) 100 K 10 K Bohm SI Hekaton OCC 2PL 1 K Percentage of Read-only Transactions