Major compaction时的scan操作

Major compaction时的scan操作

发起majorcompaction时,通过CompactSplitThread.CompactionRunner.run开始执行

-->region.compact(compaction,store)-->store.compact(compaction)-->

CompactionContext.compact,发起compact操作

CompactionContext的实例通过HStore中的storeEngine.createCompaction()生成,

默认值为DefaultStoreEngine,通过hbase.hstore.engine.class配置。

默认的CompactionContext实例为DefaultCompactionContext

DefaultCompactionContext.compact方法最终调用DefaultStoreEngine.compactor来执行

compactor的实现通过hbase.hstore.defaultengine.compactor.class配置,默认实现为DefaultCompactor

调用DefaultCompactor.compact(request);


1.根据要进行compactstorefile文件,生成对应的StoreFileScanner集合列表。

在生成StoreFileScanner实例时,每一个scanner中的ScanQueryMatchernull


2.创建StoreScanner实例,设置ScanTypeScanType.COMPACT_DROP_DELETES


privateStoreScanner(Storestore,ScanInfoscanInfo,Scanscan,

List<?extendsKeyValueScanner>scanners,ScanTypescanType,longsmallestReadPoint,

longearliestPutTs,byte[]dropDeletesFromRow,byte[]dropDeletesToRow)throwsIOException {

this(store,false,scan,null,scanInfo.getTtl(),

scanInfo.getMinVersions());

if(dropDeletesFromRow==null){

执行这里,传入的columnsnull

matcher=newScanQueryMatcher(scan,scanInfo,null,scanType,

smallestReadPoint,earliestPutTs,oldestUnexpiredTS);

}else{

matcher=newScanQueryMatcher(scan,scanInfo,null,smallestReadPoint,

earliestPutTs,oldestUnexpiredTS,dropDeletesFromRow,dropDeletesToRow);

}


ScanqueryMatcher的构造方法:

传入的columnsnull

publicScanQueryMatcher(Scanscan,ScanInfoscanInfo,

NavigableSet<byte[]>columns,ScanTypescanType,

longreadPointToUse,longearliestPutTs,longoldestUnexpiredTS){

trmintime=0,maxtime=long.maxvalue

this.tr=scan.getTimeRange();

this.rowComparator=scanInfo.getComparator();

deletes属性中的kvdelete信息为到一个新的row时,都会重新进行清空。

this.deletes=newScanDeleteTracker();

this.stopRow=scan.getStopRow();

this.startKey= KeyValue.createFirstDeleteFamilyOnRow(scan.getStartRow(),

scanInfo.getFamily());

得到filter实例

this.filter=scan.getFilter();

this.earliestPutTs=earliestPutTs;

this.maxReadPointToTrackVersions=readPointToUse;

this.timeToPurgeDeletes=scanInfo.getTimeToPurgeDeletes();

此处为的值为false

/*how to deal with deletes */

this.isUserScan=scanType== ScanType.USER_SCAN;

此处的值为false,scanInfo.getKeepDeletedCells()的值默认false,

可通过tablecolumnfmaily中配置KEEP_DELETED_CELLS属性

scan.isRaw()可通过在scansetAttribute_raw_属性,默认为false

//keep deleted cells: if compaction or raw scan

this.keepDeletedCells= (scanInfo.getKeepDeletedCells()&& !isUserScan)||scan.isRaw();

此处的值为false,此时是majorcompact,不保留delete的数据

scan.isRaw()可通过在scansetAttribute_raw_属性,默认为false

//retain deletes: if minor compaction or raw scan

this.retainDeletesInOutput=scanType== ScanType.COMPACT_RETAIN_DELETES||scan.isRaw();

此时的值为false

//seePastDeleteMarker: user initiated scans

this.seePastDeleteMarkers=scanInfo.getKeepDeletedCells()&&isUserScan;

得到查询的最大版本数,此时的scan.maxversionscanInfo.maxversion的值是相同的值

intmaxVersions=

scan.isRaw()?scan.getMaxVersions(): Math.min(scan.getMaxVersions(),

scanInfo.getMaxVersions());


生成columns属性的值为ScanWildcardColumnTracker实例,设置hasNullColumn的值为true

//Single branch to deal with two types of reads (columnsvsall in family)

if(columns ==null||columns.size()== 0) {

//there is always a null column in thewildcardcolumn query.

hasNullColumn=true;

columns属性中的index表示当前比对到的column的下标值,每比较一行时,此值会重新清空

//use a specialized scan forwildcardcolumn tracker.

this.columns=newScanWildcardColumnTracker(

scanInfo.getMinVersions(),maxVersions,oldestUnexpiredTS);

}else{

这个部分在compact时是不会执行的

//whether there is null column in the explicit column query

hasNullColumn= (columns.first().length== 0);


//We can share the ExplicitColumnTracker,diffis we reset

//between rows, not betweenstorefiles.

this.columns=newExplicitColumnTracker(columns,

scanInfo.getMinVersions(),maxVersions,oldestUnexpiredTS);

}

}


ScanQueryMatcher.match过滤kv是否包含的方法分析

在通过StoreScanner.next(kvlist,limit)得到下一行的kv集合时

调用ScanQueryMatcher.match来过滤数据的方法分析

其中match方法返回的值具体作用可参见StoreScanner中的如下方法:

publicbooleannext(List<Cell>outResult,intlimit).....


publicMatchCodematch(KeyValuekv)throwsIOException {

调用filterfilterAllRemaining方法,如果此方法返回true表示此次scan结束

if(filter !=null&&filter.filterAllRemaining()){

returnMatchCode.DONE_SCAN;

}

得到kv的值

byte[]bytes =kv.getBuffer();

KVbytes中的开始位置

intoffset =kv.getOffset();

得到key的长度

keyvalue的组成:

4

4

2

~

1

~

~

8

1

~

kenlen

vlen

rowlen

row

cflen

cf

column

timestamp

kvtype

value


intkeyLength =Bytes.toInt(bytes,offset,Bytes.SIZEOF_INT);

得到rowkey的长度记录的开始位置(不包含keylenvlen

offset+= KeyValue.ROW_OFFSET;

rowkey的长度记录的开始位置

intinitialOffset=offset;

得到rowkey的长度

shortrowLength =Bytes.toShort(bytes,offset,Bytes.SIZEOF_SHORT);

得到rowkey的开始位置

offset+= Bytes.SIZEOF_SHORT;

比较当前传入的kvrowkey部分是否与当前行中第一个kvrowkey部分相同。也就是是否是同一行的数据

intret =this.rowComparator.compareRows(row,this.rowOffset,this.rowLength,

bytes,offset,rowLength);

如果当前传入的kv中的rowkey大于当前行的kvrowkey部分,表示现在传入的kv是下一行,

结束当前next操作,(不是结束scan,是结束当次的next,表示这个next的一行数据的所有kv都查找完了)

if(ret <=-1) {

returnMatchCode.DONE;

否则表示当前传入的kv是上一行的数据,需要把当前的scanner向下移动一行

}elseif(ret >=1) {

//could optimize this, if necessary?

//Could also be called SEEK_TO_CURRENT_ROW, but this

//should be rare/never happens.

returnMatchCode.SEEK_NEXT_ROW;

}

优化配置,是否需要不执行下面流程,直接把当前的scanner向下移动一行

stickyNextRow的值为true的条件:

1.ColumnTracker.done返回为true,

2.ColumnTracker.checkColumn返回为SEEK_NEXT_ROW.

3.filter.filterKeyValue(kv);返回结果为NEXT_ROW

4.ColumnTracker.checkVersions返回为INCLUDE_AND_SEEK_NEXT_ROW

ColumnTracker的实现在scancolumnsnull或者是compactscan时为ScanWildcardColumnTracker

否则为ExplicitColumnTracker


//optimize case.

if(this.stickyNextRow)

returnMatchCode.SEEK_NEXT_ROW;

ScanWildcardColumnTracker实例中返回值为false,

ExplicitColumnTracker实例中返回值是当前的kv是否大于或等于查找的column列表的总和

if(this.columns.done()){

stickyNextRow=true;

returnMatchCode.SEEK_NEXT_ROW;

}

得到familylen的记录位置

//PassingrowLength

offset+=rowLength;

得到family的长度

//Skippingfamily

bytefamilyLength=bytes[offset];

把位置移动到family的名称记录的位置

offset+=familyLength+ 1;

得到column的长度

intqualLength=keyLength-

(offset-initialOffset)- KeyValue.TIMESTAMP_TYPE_SIZE;

得到kvtimestamp的值

longtimestamp =Bytes.toLong(bytes,initialOffset+keyLength– KeyValue.TIMESTAMP_TYPE_SIZE);

检查timestamp是否在指定的范围内,主要检查ttl是否过期

//check for early out based ontimestampalone

if(columns.isDone(timestamp)){

如果发现kvttl过期,在ScanWildcardColumnTracker实例中直接返回SEEK_NEXT_COL。这个在compact中是默认

ExplicitColumnTracker实例中检查是否有下一个column如果有返回SEEK_NEXT_COL。否则返回SEEK_NEXT_ROW

returncolumns.getNextRowOrNextColumn(bytes,offset,qualLength);

}


/*

*The delete logic is pretty complicated now.

*This is corroborated by the following:

*1. The store might be instructed to keep deleted rows around.

*2. A scan can optionally see past a delete marker now.

*3. If deleted rows are kept, we have to find out when we can

* remove the delete markers.

*4. Family delete markers are always first (regardless of their TS)

*5. Delete markers should not be counted as version

*6. Delete markers affect puts of the *same* TS

*7. Delete marker need to be version counted together with puts

* they affect

*/

得到kv的类型。

bytetype =bytes[initialOffset+keyLength– 1];

如果kv是删除的kv

if(kv.isDelete()){

在默认情况下,此keepDeletedCells值为false,这里的if检查会进去

if(!keepDeletedCells){

//first ignore delete markers if the scanner can do so, and the

//range does not include the marker

//

//during flushes andcompactionsalso ignore delete markers newer

//than thereadpointof any open scanner, this prevents deleted

//rows that could still be seen by a scanner from being collected

此时的值为true,scan中的tr默认为alltime=true

booleanincludeDeleteMarker=seePastDeleteMarkers?

tr.withinTimeRange(timestamp):

tr.withinOrAfterTimeRange(timestamp);

把删除的kv添加到DeleteTracker中。compact时的实现为ScanDeleteTracker

if(includeDeleteMarker

&&kv.getMvccVersion()<=maxReadPointToTrackVersions){

this.deletes.add(bytes,offset,qualLength,timestamp,type);

}

//Can't early out now, because DelFam come before any other keys

}

如果非minorcompact时,

或者在compactscan时,同时当前时间减去kvtimestamp还不到hbase.hstore.time.to.purge.deletes配置的时间,

默认的配置值为0,

或者kvmvcc值大于现在最大的mvcc值时。此if会进行。目前在做majorcompactscan,不进去

if(retainDeletesInOutput

|| (!isUserScan&& (EnvironmentEdgeManager.currentTimeMillis()-timestamp)<=timeToPurgeDeletes)

||kv.getMvccVersion()>maxReadPointToTrackVersions){

//always include or it is not time yet to check whether it is OK

//to purgedeltesor not

if(!isUserScan){

//if this is not a user scan (compaction), we can filter thisdeletemarkerright here

//otherwise (i.e. a "raw" scan) we fall through to normalversion andtimerangechecking

returnMatchCode.INCLUDE;

}

以下的检查通常情况不会进入

}elseif(keepDeletedCells){

if(timestamp<earliestPutTs){

//keeping delete rows, but there are no puts older than

//this delete in the store files.

returncolumns.getNextRowOrNextColumn(bytes,offset,qualLength);

}

//else: fall through and do version counting on the

//delete markers

如果kv是已经deletekv,添加到DeleteTracker后,直接返回SKIP.

}else{

returnMatchCode.SKIP;

}

//note the following next else if...

//delete marker are not subject to other delete markers

}elseif(!this.deletes.isEmpty()){

如果不是删除的KV时,检查删除的kv中是否包含此kv的版本。

a.如果KVDeleteFamily。同时当前的KVTIMESTAMP的值小于删除的KVTIMESTAMP的值,返回FAMILY_DELETED

b.如果KVDeleteFamilyVersion已经删除掉的版本(删除时指定了timestamp)。返回FAMILY_VERSION_DELETED

c.如果KV的是DeleteColumn,同时deleteTracker中包含的kv中部分qualifier的值

与传入的kv中部分qualifier的值相同。同时delete中包含的kvDeleteColumn返回COLUMN_DELETED

否则deleteTracker中包含的kv中部分qualifier的值与传入的kv中部分qualifier的值相同。

同时传入的kv中的timestamp的值是delete中的timestamp值,表示删除指定的版本,返回VERSION_DELETED

d.否则表示没有删除的情况,返回NOT_DELETED

DeleteResultdeleteResult=deletes.isDeleted(bytes,offset,qualLength,

timestamp);

switch(deleteResult){

caseFAMILY_DELETED:

caseCOLUMN_DELETED:

returncolumns.getNextRowOrNextColumn(bytes,offset,qualLength);

caseVERSION_DELETED:

caseFAMILY_VERSION_DELETED:

returnMatchCode.SKIP;

caseNOT_DELETED:

break;

default:

thrownewRuntimeException("UNEXPECTED");

}

}

检查当前传入的kvtimestamp是否在包含的时间范围内,默认的scan是所有时间都包含

inttimestampComparison=tr.compare(timestamp);

如果当前kv的时间超过了最大的时间,返回SKIP

if(timestampComparison>= 1) {

returnMatchCode.SKIP;

}elseif(timestampComparison<= -1) {

如果当前kv的时间小于了最小的时间,返回SEEK_NEXT_COL或者SEEK_NEXT_ROW

returncolumns.getNextRowOrNextColumn(bytes,offset,qualLength);

}

如果时间在正常的范围内,columns.checkColumn如果是compact时的scan此方法返回INCLUDE

其它情况请参见ExplicitColumnTracker的实现。

//STEP 1: Check if the column is part of the requested columns

MatchCodecolChecker=columns.checkColumn(bytes,offset,qualLength,type);

此处的IF检查会进入

if(colChecker==MatchCode.INCLUDE){

执行filter操作,并根据filter的响应返回相关的值,此处不在说明,比较容易看明白。

ReturnCodefilterResponse=ReturnCode.SKIP;

//STEP 2: Yes, the column is part of the requested columns. Check iffilter is present

if(filter !=null){

//STEP 3: Filter the key value and return if it filters out

filterResponse=filter.filterKeyValue(kv);

switch(filterResponse){

caseSKIP:

returnMatchCode.SKIP;

caseNEXT_COL:

returncolumns.getNextRowOrNextColumn(bytes,offset,qualLength);

caseNEXT_ROW:

stickyNextRow=true;

returnMatchCode.SEEK_NEXT_ROW;

caseSEEK_NEXT_USING_HINT:

returnMatchCode.SEEK_NEXT_USING_HINT;

default:

//Itmeans it is either include or include and seek next

break;

}

}

/*

* STEP 4: Reaching this stepmeans the column is part of the requested columns and either

* the filter is null or thefilter has returned INCLUDE or INCLUDE_AND_NEXT_COL response.

* Now check the number ofversions needed. This method call returns SKIP, INCLUDE,

* INCLUDE_AND_SEEK_NEXT_ROW,INCLUDE_AND_SEEK_NEXT_COL.

*

* FilterResponse ColumnChecker Desired behavior

* INCLUDE SKIP row has already been included, SKIP.

* INCLUDE INCLUDE INCLUDE

* INCLUDE INCLUDE_AND_SEEK_NEXT_COL INCLUDE_AND_SEEK_NEXT_COL

* INCLUDE INCLUDE_AND_SEEK_NEXT_ROW INCLUDE_AND_SEEK_NEXT_ROW

* INCLUDE_AND_SEEK_NEXT_COL SKIP row has already been included, SKIP.

* INCLUDE_AND_SEEK_NEXT_COLINCLUDE INCLUDE_AND_SEEK_NEXT_COL

* INCLUDE_AND_SEEK_NEXT_COLINCLUDE_AND_SEEK_NEXT_COL INCLUDE_AND_SEEK_NEXT_COL

* INCLUDE_AND_SEEK_NEXT_COLINCLUDE_AND_SEEK_NEXT_ROW INCLUDE_AND_SEEK_NEXT_ROW

*

* In all the above scenarios, wereturn the column checker return value except for

* FilterResponse(INCLUDE_AND_SEEK_NEXT_COL) and ColumnChecker(INCLUDE)

*/

colChecker=

columns.checkVersions(bytes,offset,qualLength,timestamp,type,

kv.getMvccVersion()>maxReadPointToTrackVersions);

//Optimizewith stickyNextRow

stickyNextRow=colChecker==MatchCode.INCLUDE_AND_SEEK_NEXT_ROW?true:stickyNextRow;

return(filterResponse==ReturnCode.INCLUDE_AND_NEXT_COL&&

colChecker==MatchCode.INCLUDE)?MatchCode.INCLUDE_AND_SEEK_NEXT_COL

:colChecker;

}

stickyNextRow= (colChecker==MatchCode.SEEK_NEXT_ROW)?true

:stickyNextRow;

returncolChecker;

}


majorminorcompact写入新storefile时的区别

如果是majorcompact的写入,会在closewriter时,

meta中写入major==true的值MAJOR_COMPACTION_KEY=true

此值主要用来控制做minorcompact时是否选择这个storefile文件。


if (writer!=null) {

writer.appendMetadata(fd.maxSeqId,request.isMajor());

writer.close();

newFiles.add(writer.getPath());

}




你可能感兴趣的:(分布式,源代码,hbase)