Can you provide a little more info on what I'm seeing here. When name is shown
for the column, are you showing me the entire byte buffer for the name or just
up to limit ?
Aaron
On 20 Apr 2011, at 05:49, Abraham Sanderson wrote:
> Ok, set up a unit test for the supercolumns which seem to have problems, I
> posted a few examples below. As I mentioned, the retrieved bytes for the
> name and value appear to have additional data; in previous tests the buffer's
> position, mark, and limit have been verified, and when I call
> column.getName(), just the bytes for the name itself are properly
> retrieved(if not I should be getting validation errors for the custom uuid
> types, correct?).
>
> Abe Sanderson
>
> get_slice for key: 80324d09-302b-4093-9708-e509091e5d8f supercolumn:
> 0faced00057372002a6c696e676f74656b2e646f6373746f72652e43617373616e647261446f63756d656e74245461726765749d0b9f071f4cb0410200024900076d5f70686173654c00066d5f6c616e677400124c6a6176612f6c616e672f537472696e673b78700000000174000564655f4445
> subcolumn: [ cf="TranslationsByTarget"
> name="78cfd525-a520-458e-8584-259415b88405"]
> colParent:ColumnParent(column_family:TranslationsByTarget, super_column:0F AC
> ED 00 05 73 72 00 2A 6C 69 6E 67 6F 74 65 6B 2E 64 6F 63 73 74 6F 72 65 2E 43
> 61 73 73 61 6E 64 72 61 44 6F 63 75 6D 65 6E 74 24 54 61 72 67 65 74 9D 0B 9F
> 07 1F 4C B0 41 02 00 02 49 00 07 6D 5F 70 68 61 73 65 4C 00 06 6D 5F 6C 61 6E
> 67 74 00 12 4C 6A 61 76 61 2F 6C 61 6E 67 2F 53 74 72 69 6E 67 3B 78 70 00 00
> 00 01 74 00 05 64 65 5F 44 45)
> predicate:SlicePredicate(column_names:[java.nio.HeapByteBuffer[pos=0 lim=17
> cap=17]])
> col: ColumnOrSuperColumn(column:Column(name:80 01 00 02 00 00 00 09 67 65 74
> 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 04 0C 00 01 0B 00 01 00 00
> 00 11 10 49 5D 01 32 73 0D 48 03 85 09 CA F1 AF 6F 60 63, value:80 01 00 02
> 00 00 00 09 67 65 74 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 04 0C
> 00 01 0B 00 01 00 00 00 11 10 49 5D 01 32 73 0D 48 03 85 09 CA F1 AF 6F 60 63
> 0B 00 02 00 00 00 11 10 FC 0A 0D 43 B1 E0 44 F9 96 AA FC EE 41 EC 40 7E,
> timestamp:1301327609539))
> col: ColumnOrSuperColumn(column:Column(name:80 01 00 02 00 00 00 09 67 65 74
> 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 04 0C 00 01 0B 00 01 00 00
> 00 11 10 49 5D 01 32 73 0D 48 03 85 09 CA F1 AF 6F 60 63 0B 00 02 00 00 00 11
> 10 FC 0A 0D 43 B1 E0 44 F9 96 AA FC EE 41 EC 40 7E 0A 00 03 00 00 01 2E FD 2B
> 7E C3 00 00 0C 00 01 0B 00 01 00 00 00 11 10 78 CF D5 25 A5 20 45 8E 85 84 25
> 94 15 B8 84 05, value:80 01 00 02 00 00 00 09 67 65 74 5F 73 6C 69 63 65 00
> 00 00 02 0F 00 00 0C 00 00 00 04 0C 00 01 0B 00 01 00 00 00 11 10 49 5D 01 32
> 73 0D 48 03 85 09 CA F1 AF 6F 60 63 0B 00 02 00 00 00 11 10 FC 0A 0D 43 B1 E0
> 44 F9 96 AA FC EE 41 EC 40 7E 0A 00 03 00 00 01 2E FD 2B 7E C3 00 00 0C 00 01
> 0B 00 01 00 00 00 11 10 78 CF D5 25 A5 20 45 8E 85 84 25 94 15 B8 84 05 0B 00
> 02 00 00 00 11 10..., timestamp:1301327602293))
> col: ColumnOrSuperColumn(column:Column(name:80 01 00 02 00 00 00 09 67 65 74
> 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 04 0C 00 01 0B 00 01 00 00
> 00 11 10 49 5D 01 32 73 0D 48 03 85 09 CA F1 AF 6F 60 63 0B 00 02 00 00 00 11
> 10 FC 0A 0D 43 B1 E0 44 F9 96 AA FC EE 41 EC 40 7E 0A 00 03 00 00 01 2E FD 2B
> 7E C3 00 00 0C 00 01 0B 00 01 00 00 00 11 10 78 CF D5 25 A5 20 45 8E 85 84 25
> 94 15 B8 84 05 0B 00 02 00 00 00 11 10..., value:80 01 00 02 00 00 00 09 67
> 65 74 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 04 0C 00 01 0B 00 01
> 00 00 00 11 10 49 5D 01 32 73 0D 48 03 85 09 CA F1 AF 6F 60 63 0B 00 02 00 00
> 00 11 10 FC 0A 0D 43 B1 E0 44 F9 96 AA FC EE 41 EC 40 7E 0A 00 03 00 00 01 2E
> FD 2B 7E C3 00 00 0C 00 01 0B 00 01 00 00 00 11 10 78 CF D5 25 A5 20 45 8E 85
> 84 25 94 15 B8 84 05 0B 00 02 00 00 00 11 10..., timestamp:1301327589704))
> col: ColumnOrSuperColumn(column:Column(name:80 01 00 02 00 00 00 09 67 65 74
> 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 04 0C 00 01 0B 00 01 00 00
> 00 11 10 49 5D 01 32 73 0D 48 03 85 09 CA F1 AF 6F 60 63 0B 00 02 00 00 00 11
> 10 FC 0A 0D 43 B1 E0 44 F9 96 AA FC EE 41 EC 40 7E 0A 00 03 00 00 01 2E FD 2B
> 7E C3 00 00 0C 00 01 0B 00 01 00 00 00 11 10 78 CF D5 25 A5 20 45 8E 85 84 25
> 94 15 B8 84 05 0B 00 02 00 00 00 11 10..., value:80 01 00 02 00 00 00 09 67
> 65 74 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 04 0C 00 01 0B 00 01
> 00 00 00 11 10 49 5D 01 32 73 0D 48 03 85 09 CA F1 AF 6F 60 63 0B 00 02 00 00
> 00 11 10 FC 0A 0D 43 B1 E0 44 F9 96 AA FC EE 41 EC 40 7E 0A 00 03 00 00 01 2E
> FD 2B 7E C3 00 00 0C 00 01 0B 00 01 00 00 00 11 10 78 CF D5 25 A5 20 45 8E 85
> 84 25 94 15 B8 84 05 0B 00 02 00 00 00 11 10..., timestamp:1301327594118))
>
>
> get_slice for key: d1c7f6b9-1425-4fab-b074-5574c54cae08 supercolumn:
> 0faced00057372002a6c696e676f74656b2e646f6373746f72652e43617373616e647261446f63756d656e74245461726765749d0b9f071f4cb0410200024900076d5f70686173654c00066d5f6c616e677400124c6a6176612f6c616e672f537472696e673b78700000000174000564655f4445
> subcolumn: [ cf="TranslationsByTarget"
> name="b2f33b97-69f4-45ec-ad87-dd14ee60d719"]
> colParent:ColumnParent(column_family:TranslationsByTarget, super_column:0F AC
> ED 00 05 73 72 00 2A 6C 69 6E 67 6F 74 65 6B 2E 64 6F 63 73 74 6F 72 65 2E 43
> 61 73 73 61 6E 64 72 61 44 6F 63 75 6D 65 6E 74 24 54 61 72 67 65 74 9D 0B 9F
> 07 1F 4C B0 41 02 00 02 49 00 07 6D 5F 70 68 61 73 65 4C 00 06 6D 5F 6C 61 6E
> 67 74 00 12 4C 6A 61 76 61 2F 6C 61 6E 67 2F 53 74 72 69 6E 67 3B 78 70 00 00
> 00 01 74 00 05 64 65 5F 44 45)
> predicate:SlicePredicate(column_names:[java.nio.HeapByteBuffer[pos=0 lim=17
> cap=17]])
> col: ColumnOrSuperColumn(column:Column(name:80 01 00 02 00 00 00 09 67 65 74
> 5F 73 6C 69 63 65 00 00 00 04 0F 00 00 0C 00 00 00 02 0C 00 01 0B 00 01 00 00
> 00 11 10 7C 2F 5D 5B B3 70 42 E1 A6 A2 77 FC 72 14 40 FE, value:80 01 00 02
> 00 00 00 09 67 65 74 5F 73 6C 69 63 65 00 00 00 04 0F 00 00 0C 00 00 00 02 0C
> 00 01 0B 00 01 00 00 00 11 10 7C 2F 5D 5B B3 70 42 E1 A6 A2 77 FC 72 14 40 FE
> 0B 00 02 00 00 00 11 10 B4 64 74 19 F9 44 4E A3 A5 F9 06 32 67 DB 33 19,
> timestamp:1301324860465))
> col: ColumnOrSuperColumn(column:Column(name:80 01 00 02 00 00 00 09 67 65 74
> 5F 73 6C 69 63 65 00 00 00 04 0F 00 00 0C 00 00 00 02 0C 00 01 0B 00 01 00 00
> 00 11 10 7C 2F 5D 5B B3 70 42 E1 A6 A2 77 FC 72 14 40 FE 0B 00 02 00 00 00 11
> 10 B4 64 74 19 F9 44 4E A3 A5 F9 06 32 67 DB 33 19 0A 00 03 00 00 01 2E FD 01
> 8C 31 00 00 0C 00 01 0B 00 01 00 00 00 11 10 B2 F3 3B 97 69 F4 45 EC AD 87 DD
> 14 EE 60 D7 19, value:80 01 00 02 00 00 00 09 67 65 74 5F 73 6C 69 63 65 00
> 00 00 04 0F 00 00 0C 00 00 00 02 0C 00 01 0B 00 01 00 00 00 11 10 7C 2F 5D 5B
> B3 70 42 E1 A6 A2 77 FC 72 14 40 FE 0B 00 02 00 00 00 11 10 B4 64 74 19 F9 44
> 4E A3 A5 F9 06 32 67 DB 33 19 0A 00 03 00 00 01 2E FD 01 8C 31 00 00 0C 00 01
> 0B 00 01 00 00 00 11 10 B2 F3 3B 97 69 F4 45 EC AD 87 DD 14 EE 60 D7 19 0B 00
> 02 00 00 00 11 10..., timestamp:1301325719735))
>
>
> get_slice for key: 18b4acd1-5491-44d3-aaa1-b725f51d1c3b supercolumn:
> 0faced00057372002a6c696e676f74656b2e646f6373746f72652e43617373616e647261446f63756d656e74245461726765749d0b9f071f4cb0410200024900076d5f70686173654c00066d5f6c616e677400124c6a6176612f6c616e672f537472696e673b787000000001740005706c5f504c
> subcolumn: [ cf="TranslationsByTarget"
> name="3da78c49-a8aa-4fdb-8238-1ade458426b5"]
> colParent:ColumnParent(column_family:TranslationsByTarget, super_column:0F AC
> ED 00 05 73 72 00 2A 6C 69 6E 67 6F 74 65 6B 2E 64 6F 63 73 74 6F 72 65 2E 43
> 61 73 73 61 6E 64 72 61 44 6F 63 75 6D 65 6E 74 24 54 61 72 67 65 74 9D 0B 9F
> 07 1F 4C B0 41 02 00 02 49 00 07 6D 5F 70 68 61 73 65 4C 00 06 6D 5F 6C 61 6E
> 67 74 00 12 4C 6A 61 76 61 2F 6C 61 6E 67 2F 53 74 72 69 6E 67 3B 78 70 00 00
> 00 01 74 00 05 70 6C 5F 50 4C)
> predicate:SlicePredicate(column_names:[java.nio.HeapByteBuffer[pos=0 lim=17
> cap=17]])
> col: ColumnOrSuperColumn(column:Column(name:80 01 00 02 00 00 00 09 67 65 74
> 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 03 0C 00 01 0B 00 01 00 00
> 00 11 10 24 D4 2C 7F 2D C3 4A 80 B3 FF 5B A3 77 AF 2E BD, value:80 01 00 02
> 00 00 00 09 67 65 74 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 03 0C
> 00 01 0B 00 01 00 00 00 11 10 24 D4 2C 7F 2D C3 4A 80 B3 FF 5B A3 77 AF 2E BD
> 0B 00 02 00 00 00 11 10 62 58 73 23 CB 37 4F B5 BD DD BC F5 1E 7F E7 65,
> timestamp:1301000346861))
> col: ColumnOrSuperColumn(column:Column(name:80 01 00 02 00 00 00 09 67 65 74
> 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 03 0C 00 01 0B 00 01 00 00
> 00 11 10 24 D4 2C 7F 2D C3 4A 80 B3 FF 5B A3 77 AF 2E BD 0B 00 02 00 00 00 11
> 10 62 58 73 23 CB 37 4F B5 BD DD BC F5 1E 7F E7 65 0A 00 03 00 00 01 2E E9 A9
> DC ED 00 00 0C 00 01 0B 00 01 00 00 00 11 10 3D A7 8C 49 A8 AA 4F DB 82 38 1A
> DE 45 84 26 B5, value:80 01 00 02 00 00 00 09 67 65 74 5F 73 6C 69 63 65 00
> 00 00 02 0F 00 00 0C 00 00 00 03 0C 00 01 0B 00 01 00 00 00 11 10 24 D4 2C 7F
> 2D C3 4A 80 B3 FF 5B A3 77 AF 2E BD 0B 00 02 00 00 00 11 10 62 58 73 23 CB 37
> 4F B5 BD DD BC F5 1E 7F E7 65 0A 00 03 00 00 01 2E E9 A9 DC ED 00 00 0C 00 01
> 0B 00 01 00 00 00 11 10 3D A7 8C 49 A8 AA 4F DB 82 38 1A DE 45 84 26 B5 0B 00
> 02 00 00 00 11 10..., timestamp:1301000346885))
> col: ColumnOrSuperColumn(column:Column(name:80 01 00 02 00 00 00 09 67 65 74
> 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 03 0C 00 01 0B 00 01 00 00
> 00 11 10 24 D4 2C 7F 2D C3 4A 80 B3 FF 5B A3 77 AF 2E BD 0B 00 02 00 00 00 11
> 10 62 58 73 23 CB 37 4F B5 BD DD BC F5 1E 7F E7 65 0A 00 03 00 00 01 2E E9 A9
> DC ED 00 00 0C 00 01 0B 00 01 00 00 00 11 10 3D A7 8C 49 A8 AA 4F DB 82 38 1A
> DE 45 84 26 B5 0B 00 02 00 00 00 11 10..., value:80 01 00 02 00 00 00 09 67
> 65 74 5F 73 6C 69 63 65 00 00 00 02 0F 00 00 0C 00 00 00 03 0C 00 01 0B 00 01
> 00 00 00 11 10 24 D4 2C 7F 2D C3 4A 80 B3 FF 5B A3 77 AF 2E BD 0B 00 02 00 00
> 00 11 10 62 58 73 23 CB 37 4F B5 BD DD BC F5 1E 7F E7 65 0A 00 03 00 00 01 2E
> E9 A9 DC ED 00 00 0C 00 01 0B 00 01 00 00 00 11 10 3D A7 8C 49 A8 AA 4F DB 82
> 38 1A DE 45 84 26 B5 0B 00 02 00 00 00 11 10..., timestamp:1301000346836))
>
> On Mon, Apr 18, 2011 at 5:41 PM, aaron morton <aa...@thelastpickle.com> wrote:
> Can you could provide an example of a get_slice request that failed and the
> columns that were returned, so we can see the actual bytes for the super
> column and column names.
>
> Aaron
>
>
> On 19 Apr 2011, at 09:26, Abraham Sanderson wrote:
>
>> I wish it were consistent enough that the answer were simple... It varies
>> between just the requested subcolumn to all subcolumns. It always does
>> return the columns in order, and the requested column is always one of the
>> columns returned. However, the slice start is not consistently in the same
>> place(like n+1 or n-1). For example, if I have CF['key']['supercolumn'
>> ['a','b','c','d','e']], and query for 'c', sometimes i get a slice with 'a',
>> 'b', 'c', other times its 'b', 'c', 'd', sometimes 'c', 'd'. When the
>> column name is closer to the end of the range('d' or 'e'), sometimes it
>> justs a slice with the column. The sporadic behavior makes me think that
>> it's a race condition, but the behavior linked to the column range makes we
>> think I'm overrunning the buffer somewhere. I at first suspected that I was
>> inadvertently making modifications to the buffers in application code during
>> serialization/deserialization, so I did the tests in the cli. This limits
>> it to just cassandra/thrift code and my custom types. Am I missing some
>> other factor? While debugging I have noticed that the byte buffers contain
>> more than they used to; it looks to me like tokens that contain parts of the
>> thrift response. I'd see strings like
>> "???get_slice???Foo??7c2f5d5b-b370-42e1-a6a2-77fc721440fe????" Is it
>> possible that I am inadvertently using a reserved token or something on my
>> supercolumn name and this is screwing with the slice command?
>>
>> Abe
>>
>> On Mon, Apr 18, 2011 at 2:55 PM, aaron morton <aa...@thelastpickle.com>
>> wrote:
>> When you run the get_slice which columns are returned ?
>>
>>
>> Aaron
>>
>> On 19 Apr 2011, at 04:12, Abraham Sanderson wrote:
>>
>>> Ok, I made the changes and tried again. Here is the before modifying my
>>> method using a simple get, confirmed the same output in the cli:
>>>
>>> DEBUG [pool-1-thread-2] 2011-04-18 09:37:23,910 CassandraServer.java (line
>>> 279) get
>>> DEBUG [pool-1-thread-2] 2011-04-18 09:37:23,911 StorageProxy.java (line
>>> 322) Command/ConsistencyLevel is SliceByNamesReadCommand(table='DocStore',
>>> key=64316337663662392d313432352d346661622d623037342d353537346335346361653038,
>>> columnParent='QueryPath(columnFamilyName='Tran
>>> slationsByTarget', superColumnName='java.nio.HeapByteBuffer[pos=95 lim=211
>>> cap=244]', columnName='null')',
>>> columns=[7c2f5d5b-b370-42e1-a6a2-77fc721440fe,])/ALL
>>> DEBUG [pool-1-thread-2] 2011-04-18 09:37:23,911 ReadCallback.java (line 84)
>>> Blockfor/repair is 1/true; setting up requests to localhost/127.0.0.1
>>> DEBUG [pool-1-thread-2] 2011-04-18 09:37:23,911 StorageProxy.java (line
>>> 345) reading data locally
>>> DEBUG [ReadStage:4] 2011-04-18 09:37:23,911 StorageProxy.java (line 450)
>>> LocalReadRunnable reading SliceByNamesReadCommand(table='DocStore',
>>> key=64316337663662392d313432352d346661622d623037342d353537346335346361653038,
>>> columnParent='QueryPath(columnFamilyName='Translatio
>>> nsByTarget', superColumnName='java.nio.HeapByteBuffer[pos=95 lim=211
>>> cap=244]', columnName='null')',
>>> columns=[7c2f5d5b-b370-42e1-a6a2-77fc721440fe,])
>>> DEBUG [pool-1-thread-2] 2011-04-18 09:37:23,912 StorageProxy.java (line
>>> 395) Read: 1 ms.
>>> ERROR [pool-1-thread-2] 2011-04-18 09:37:23,912 Cassandra.java (line 2665)
>>> Internal error processing get
>>> java.lang.AssertionError
>>> at
>>> org.apache.cassandra.thrift.CassandraServer.get(CassandraServer.java:300)
>>> at
>>> org.apache.cassandra.thrift.Cassandra$Processor$get.process(Cassandra.java:2655)
>>> at
>>> org.apache.cassandra.thrift.Cassandra$Processor.process(Cassandra.java:2555)
>>> at
>>> org.apache.cassandra.thrift.CustomTThreadPoolServer$WorkerProcess.run(CustomTThreadPoolServer.java:206)
>>> at
>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110)
>>> at
>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603)
>>> at java.lang.Thread.run(Thread.java:636)
>>>
>>> And here is the after...it succeeds here but still gives me multiple
>>> subcolumns in the response. Same behavior, it seems, I'm just sidestepping
>>> the original AssertionError:
>>>
>>> DEBUG [pool-1-thread-6] 2011-04-18 09:50:26,617 CassandraServer.java (line
>>> 232) get_slice
>>> DEBUG [pool-1-thread-6] 2011-04-18 09:50:26,617 StorageProxy.java (line
>>> 322) Command/ConsistencyLevel is SliceByNamesReadCommand(table='DocStore',
>>> key=64316337663662392d313432352d346661622d623037342d353537346335346361653038,
>>> columnParent='QueryPath(columnFamilyName='TranslationsByTarget',
>>> superColumnName='java.nio.HeapByteBuffer[pos=101 lim=217 cap=259]',
>>> columnName='null')', columns=[7c2f5d5b-b370-42e1-a6a2-77fc721440fe,])/ALL
>>> DEBUG [pool-1-thread-6] 2011-04-18 09:50:26,617 ReadCallback.java (line 84)
>>> Blockfor/repair is 1/true; setting up requests to localhost/127.0.0.1
>>> DEBUG [pool-1-thread-6] 2011-04-18 09:50:26,617 StorageProxy.java (line
>>> 345) reading data locally
>>> DEBUG [ReadStage:3] 2011-04-18 09:50:26,618 StorageProxy.java (line 450)
>>> LocalReadRunnable reading SliceByNamesReadCommand(table='DocStore',
>>> key=64316337663662392d313432352d346661622d623037342d353537346335346361653038,
>>> columnParent='QueryPath(columnFamilyName='TranslationsByTarget',
>>> superColumnName='java.nio.HeapByteBuffer[pos=101 lim=217 cap=259]',
>>> columnName='null')', columns=[7c2f5d5b-b370-42e1-a6a2-77fc721440fe,])
>>> DEBUG [pool-1-thread-6] 2011-04-18 09:50:26,618 StorageProxy.java (line
>>> 395) Read: 0 ms.
>>>
>>> My comparators are relatively simple. Basically I have a schema that
>>> required heterogenous columns, but I needed to be able to deserialize them
>>> in unique ways. So there is always a type byte that precedes the bytes of
>>> the data. The supercolumn in this case is a general data type, which
>>> happens to represent a serializable object:
>>>
>>> public void validate(ByteBuffer bytes)
>>> throws MarshalException
>>> {
>>> if(bytes.remaining() == 0)
>>> return;
>>>
>>> validateDataType(bytes.get(bytes.position()));
>>> return;
>>> }
>>>
>>> public int compare(ByteBuffer bytes1, ByteBuffer bytes2)
>>> {
>>> if (bytes1.remaining() == 0)
>>> return bytes2.remaining() == 0 ? 0 : -1;
>>> else if (bytes2.remaining() == 0)
>>> return 1;
>>> else
>>> {
>>> // compare type bytes
>>>
>>>
>>>
>>> byte T1 = bytes1.get(bytes1.position());
>>> byte T2 = bytes2.get(bytes2.position());
>>> if (T1 != T2)
>>> return (T1 - T2);
>>>
>>> // compare values
>>>
>>>
>>>
>>> return ByteBufferUtil.compareUnsigned(bytes1, bytes2);
>>> }
>>> }
>>>
>>> The subcolumn is similar...just a UUID with a type byte prefix:
>>>
>>> public void validate(ByteBuffer bytes)
>>> throws MarshalException
>>> {
>>> if(bytes.remaining() == 0)
>>> return;
>>>
>>> validateDataType(bytes.get(bytes.position()));
>>> if((bytes.remaining() - 1) == 0)
>>> return;
>>> else if((bytes.remaining() - 1) != 16)
>>> throw new MarshalException("UUID value must be exactly 16 bytes");
>>> }
>>>
>>> public int compare(ByteBuffer bytes1, ByteBuffer bytes2)
>>> {
>>> if (bytes1.remaining() == 0)
>>> return bytes2.remaining() == 0 ? 0 : -1;
>>> else if (bytes2.remaining() == 0)
>>> return 1;
>>> else
>>> {
>>> // compare type bytes
>>>
>>>
>>>
>>> byte T1 = bytes1.get(bytes1.position());
>>> byte T2 = bytes2.get(bytes2.position());
>>> if (T1 != T2)
>>> return (T1 - T2);
>>>
>>> // compare values
>>>
>>>
>>>
>>> UUID U1 = getUUID(bytes1, bytes1.position()+1);
>>> UUID U2 = getUUID(bytes2, bytes2.position()+1);
>>> return U1.compareTo(U2);
>>> }
>>> }
>>>
>>> static UUID getUUID(ByteBuffer bytes, int pos)
>>> {
>>> long msBits = bytes.getLong(pos);
>>> long lsBits = bytes.getLong(pos+8);
>>> return new UUID(msBits, lsBits);
>>> }
>>>
>>> All of my buffer reads are done by index, the position shouldn't be
>>> changing at all.
>>>
>>> Abe Sanderson
>>>
>>> On Sat, Apr 16, 2011 at 5:38 PM, aaron morton <aa...@thelastpickle.com>
>>> wrote:
>>> Can you run the same request as a get_slice naming the column in the
>>> SlicePredicate and see what comes back ?
>>>
>>> Can you reproduce the fault with logging set at DEBUG and send the logs ?
>>>
>>> Also, whats the compare function like for your custom type ?
>>>
>>> Cheers
>>> Aaron
>>>
>>>
>>> On 16 Apr 2011, at 07:34, Abraham Sanderson wrote:
>>>
>>> > I'm having some issues with a few of my ColumnFamilies after a cassandra
>>> > upgrade/import from 0.6.1 to 0.7.4. I followed the instructions to
>>> > upgrade and everything seem to work OK...until I got into the application
>>> > and noticed some wierd behavior. I was getting the following stacktrace
>>> > in cassandra occassionally when I did get operations for a single
>>> > subcolumn for some of the Super type CFs:
>>> >
>>> > ERROR 12:56:05,669 Internal error processing get
>>> > java.lang.AssertionError
>>> > at org.apache.cassandra.thrift.
>>> > CassandraServer.get(CassandraServer.java:300)
>>> > at
>>> > org.apache.cassandra.thrift.Cassandra$Processor$get.process(Cassandra.java:2655)
>>> > at
>>> > org.apache.cassandra.thrift.Cassandra$Processor.process(Cassandra.java:2555)
>>> > at
>>> > org.apache.cassandra.thrift.CustomTThreadPoolServer$WorkerProcess.run(CustomTThreadPoolServer.java:206)
>>> > at
>>> > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110)
>>> > at
>>> > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603)
>>> > at java.lang.Thread.run(Thread.java:636)
>>> >
>>> > The assertion that is failing is the check that only one column is
>>> > retrieved by the get. I did some debugging with the cli and a remote
>>> > debugger and found a few interesting patterns. First, the problem does
>>> > not seem consistently duplicatable. If one supercolumn is affected
>>> > though, it will happen more frequently for subcolumns that when sorted
>>> > appear at the beginning of the range. For columns near the end of the
>>> > range, it seems to be more intermittent, and almost never occurs when I
>>> > step through the code line by line. The only factor I can think of that
>>> > might cause issues is that I am using custom data types for all
>>> > supercolumns and columns. I originally thought I might be reading past
>>> > the end of the ByteBuffer, but I have quadrupled checked that this is not
>>> > the case.
>>> >
>>> > Abe Sanderson
>>>
>>>
>>
>>
>
>
