Discussing the Apache Cassandra 3.0 storage engine, and it's performance characteristics.

1. SF CASSANDRA USERS MARCH 2016
CQL PERFORMANCE WITH APACHE
CASSANDRA 3.0
Aaron Morton
@aaronmorton
CEO
Licensed under a Creative Commons Attribution-NonCommercial 3.0 New Zealand License

2. AboutThe Last Pickle.
Work with clients to deliver and improve Apache Cassandra
based solutions.
Apache Cassandra Committer and DataStax MVPs.
Based in New Zealand,Australia, France & USA.

3. How We Got Here
Storage Engine 3.0
Write Path
Read Path

4. How We Got Here
Way back in 2011…

5. 2011
Blog: Cassandra Query Plans
http://thelastpickle.com/blog/2011/07/04/
Cassandra-Query-Plans.html

6. 2012
Talk:Technical Deep Dive -
Query Performance
https://www.youtube.com/watch?
v=gomOKhMV0zc

7. 2012
Explain Read & Write
performance in 45 minutes.

8. Skip Forward to 2016
Blog: Introduction To The
Apache Cassandra 3.x Storage
Engine
http://thelastpickle.com/blog/2016/03/04/introductiont-to-
the-apache-cassandra-3-storage-engine.html

9. Skip Forward to 2016
“Why don’t I do another talk
about Cassandra
performance.”

10. Skip Forward to 2016
It was a busy 4 years…

11. Skip Forward to 2016
CQL 3, Collection Types,
UDTs, UDF’s, UDA’s,
MaterialisedViews,Triggers,
SASI,…

12. Skip Forward to 2016
Explain Read & Write
performance in 45 minutes.

13. So Lets Avoid
CQL 3, Collection Types,
UDTs, UDF’s, UDA’s,
MaterialisedViews,Triggers,
SASI,…

14. How We Got Here
Storage Engine 3.0
Write Path
Read Path

15. High Level Storage Engine 3.0

16. Storage Engine 3.0 Files
Data.db
Index.db
Filter.db

17. Storage Engine 3.0 Files
CompressionInfo.db
Statistics.db
Digest.crc32
CRC.db
Summary.db
TOC.txt

18. CQL Recap
create table my_table (
partition_1 text,
cluster_1 text,
foo text,
bar text,
baz text,
PRIMARY KEY (partition_1, cluster_1)
);

19. CQL Recap
WARNING:
FAKE DATA AHEAD

20. CQL WithThrift Pre 3.0
[default@dev] list my_table;
-------------------
RowKey: part_a
=> (column=clust_a:, value=, timestamp=1357…739000)
=> (column=clust_a:foo, value=some foo, timestamp=1357…739000)
=> (column=clust_a:bar, value=and bar, timestamp=1357…739000)
=> (column=clust_a:baz, value=no baz, timestamp=1357…739000)
=> (column=clust_b:, value=, timestamp=1357…739000)
=> (column=clust_b:foo, value=no foo, timestamp=1357…739000)
=> (column=clust_b:bar, value=no bar, timestamp=1357…739000)
=> (column=clust_b:baz, value=lots baz, timestamp=1357…739000)

21. CQL Pre 3.0
Clustering Keys Repeated
Column Names Repeated
Timestamps Repeated
Fixed Width Encoding
No Knowledge Of Row Contents

22. Storage Engine 3.0 Improvements
Delta Encoding
Variable Int Encoding
Clustering Written Once
Aggregated Metadata
Cell Presence

23. SerializationHeader
For each SSTable*.
Stored in each SSTable.
Held in memory.

24. SerializationHeader
public class SerializationHeader
{
private final AbstractType<?> keyType;
private final List<AbstractType<?>>
clusteringTypes;
private final PartitionColumns columns;
private final EncodingStats stats;
…
}

25. EncodingStats
Collected on the fly by the
Memtable.

26. EncodingStats
public class EncodingStats
{
public final long minTimestamp;
public final int minLocalDeletionTime;
public final int minTTL;
…
}

27. SerializationHeader
public class SerializationHeader
{
public void writeTimestamp(long timestamp,
DataOutputPlus out) throws IOException
{
out.writeUnsignedVInt(timestamp -
stats.minTimestamp);
}
…
}

28. VIntCoding
public class VIntCoding
{
public static void writeUnsignedVInt(long value, DataOutput
output) throws IOException {
int size = VIntCoding.computeUnsignedVIntSize(value);
if (size == 1)
{
output.write((int)value);
return;
}
output.write(VIntCoding.encodeVInt(value, size), 0,
size);
}

29. Storage Engine 3.0 Improvements
Delta Encoding
Variable Int Encoding
Clustering Written Once
Aggregated Metadata
Cell Presence

30. CQL WithThrift Pre 3.0
[default@dev] list my_table;
-------------------
RowKey: part_a
=> (column=clust_a:, value=, timestamp=1357…739000)
=> (column=clust_a:foo, value=some foo, timestamp=1357…739000)
=> (column=clust_a:bar, value=and bar, timestamp=1357…739000)
=> (column=clust_a:baz, value=no baz, timestamp=1357…739000)
=> (column=clust_b:, value=, timestamp=1357…739000)
=> (column=clust_b:foo, value=no foo, timestamp=1357…739000)
=> (column=clust_b:bar, value=no bar, timestamp=1357…739000)
=> (column=clust_b:baz, value=lots baz, timestamp=1357…739000)

31. Storage Engine 3.0 Data.db

32. Storage Engine 3.0 Partition Header
Partition Key
Partition Deletion Information

33. Storage Engine 3.0 Partition Header

34. Storage Engine 3.0 Row
Clustering Information
Row Level Liveness
Row Level Deletion
Column Presence
Columns

35. Storage Engine 3.0 Row

36. Storage Engine 3.0 Clustering Block
Clustering Cell Presence
Clustering Cells

37. Storage Engine 3.0 Clustering Block

38. Storage Engine 3.0 Improvements
Delta Encoding
Variable Int Encoding
Clustering Written Once
Aggregated Cell Metadata
Cell Presence

39. CQL WithThrift Pre 3.0
[default@dev] list my_table;
-------------------
RowKey: part_a
=> (column=clust_a:, value=, timestamp=1357…739000)
=> (column=clust_a:foo, value=some foo, timestamp=1357…739000)
=> (column=clust_a:bar, value=and bar, timestamp=1357…739000)
=> (column=clust_a:baz, value=no baz, timestamp=1357…739000)
=> (column=clust_b:, value=, timestamp=1357…739000)
=> (column=clust_b:foo, value=no foo, timestamp=1357…739000)
=> (column=clust_b:bar, value=no bar, timestamp=1357…739000)
=> (column=clust_b:baz, value=lots baz, timestamp=1357…739000)

40. Aggregated Cell Metadata
Only store CellTimestamp,TTL, and
Local DeletionTime if different to
the Row.

41. Aggregated Cell Metadata
Simple Cell Component Byte Size
Flags 1
Optional Cell Timestamp (delta) varint 1…n
Optional Cell Local Deletion Time (delta) varint 1…n
Optional Cell TTL (delta) varint 1…n
Fixed Width Cell Value Byte Size
Value 1…n
Optional Cell Value See Below
Variable Width Cell Value Byte Size
Value Length varint 1…n
Value 1…n
Apache Cassandra 3.0 Storage Engine

42. Storage Engine 3.0 Improvements
Delta Encoding
Variable Int Encoding
Clustering Written Once
Aggregated Cell Metadata
Cell Presence

43. Cell Presence
SSTable stores list of Cells in this
SSTable.
Rows stores bitmap of Cells in this
Row, with reference to SSTable.

44. Storage Engine 3.0 Row

45. Remember Where We Came From
[default@dev] list my_table;
-------------------
RowKey: part_a
=> (column=clust_a:, value=, timestamp=1357…739000)
=> (column=clust_a:foo, value=some foo, timestamp=1357…739000)
=> (column=clust_a:bar, value=and bar, timestamp=1357…739000)
=> (column=clust_a:baz, value=no baz, timestamp=1357…739000)
=> (column=clust_b:, value=, timestamp=1357…739000)
=> (column=clust_b:foo, value=no foo, timestamp=1357…739000)
=> (column=clust_b:bar, value=no bar, timestamp=1357…739000)
=> (column=clust_b:baz, value=lots baz, timestamp=1357…739000)

46. How We Got Here
Storage Engine 3.0
Write Path
Read Path

47. Write Path
Commit Log
Merge Into Memtable

48. Commit Log
Allocate space in the current
commit log segment.

49. Allocate Segment
o.a.c.m.
CommitLog.WaitingOnSegmentAllocation.
95thPercentile

50. Merge Into Memtable
Find the Partition.
Loop trying to update the
Rows in it using CAS.

51. Merge Into Memtable
If more than 10MB wasted
allocations move to
Pessimistic locking on the
Partition object.

52. How We Got Here
Storage Engine 3.0
Write Path
Read Path

53. Read Paths
Ignoring Index Read paths.

54. Read Commands
PartitionRangeReadCommand
SinglePartitionReadCommand

55. AbstractClusteringIndexFilter
ClusteringIndexNamesFilter
(When we know the column names.)
ClusteringIndexSliceFilter
(When we do not know the column names.)

56. ClusteringIndexNamesFilter
When we know what
Columns to select, we know
when the search is over.

57. ClusteringIndexNamesFilter
1. Get Partition From Memtables.
2. Filter named columns into a temporary
result.
3. Select SSTables that may contain Partition
Key.
4. Order in descending timestamp order.
5. Read from SSTables in order.

58. Names Filter Short Circuits
If result has a Partition Deletion
newer than next SSTable max
timestamp.
Stop Search.

59. Names Filter Short Circuits
If read all Columns and max
timestamp of next SSTable less than
selected Columns min timestamp.
Stop Search.

60. Names Filter Short Circuits
Note: list of Columns
remaining to select is pruned
after every SSTable is read
based on max timestamp.

61. Names Filter Short Circuits
If search clustering value not within
clustering range in the SSTable.
Skip SSTable.

62. Names Filter Short Circuits
If SSTable Cell not in search set.
Skip reading value.

63. ClusteringIndexSliceFilter
When we do not know which
columns to select, the search
ends when it is exhausted.

64. ClusteringIndexSliceFilter
Used with:
Distinct.
Not all clustering columns
restricted.

65. ClusteringIndexSliceFilter
1. Get Partition From Memtables.
2. Create Iterators for Partitions.
3. Select SSTables that may contain Partition
Key.
4. Order in reverse max timestamp order.
5. Create Iterators for SSTables in order.

66. Slice Filter Short Circuits
If SSTable max timestamp is before
max seen Partition Deletion
timestamp.
Stop Search.

67. Names Filter Short Circuits
If search clustering value not within
clustering range in the SSTable.
Skip SSTable.

68. So…
3.x is awesome.
Starting using it as soon as
possible.

69. Thanks.

70. Aaron Morton
@aaronmorton
Co-Founder & Principal Consultant
www.thelastpickle.com