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Posted to commits@hbase.apache.org by bu...@apache.org on 2016/07/05 23:54:41 UTC
[42/52] [partial] hbase-site git commit: Published site at
29c46c4834a3f96e9fca33cb16bc7f3748fcd60c.
http://git-wip-us.apache.org/repos/asf/hbase-site/blob/6444c276/apidocs/src-html/org/apache/hadoop/hbase/mapreduce/TableInputFormatBase.html
----------------------------------------------------------------------
diff --git a/apidocs/src-html/org/apache/hadoop/hbase/mapreduce/TableInputFormatBase.html b/apidocs/src-html/org/apache/hadoop/hbase/mapreduce/TableInputFormatBase.html
index e36ae5f..7003255 100644
--- a/apidocs/src-html/org/apache/hadoop/hbase/mapreduce/TableInputFormatBase.html
+++ b/apidocs/src-html/org/apache/hadoop/hbase/mapreduce/TableInputFormatBase.html
@@ -283,384 +283,385 @@
<span class="sourceLineNo">275</span> if (!includeRegionInSplit(keys.getFirst()[i], keys.getSecond()[i])) {<a name="line.275"></a>
<span class="sourceLineNo">276</span> continue;<a name="line.276"></a>
<span class="sourceLineNo">277</span> }<a name="line.277"></a>
-<span class="sourceLineNo">278</span> HRegionLocation location = getRegionLocator().getRegionLocation(keys.getFirst()[i], false);<a name="line.278"></a>
-<span class="sourceLineNo">279</span> // The below InetSocketAddress creation does a name resolution.<a name="line.279"></a>
-<span class="sourceLineNo">280</span> InetSocketAddress isa = new InetSocketAddress(location.getHostname(), location.getPort());<a name="line.280"></a>
-<span class="sourceLineNo">281</span> if (isa.isUnresolved()) {<a name="line.281"></a>
-<span class="sourceLineNo">282</span> LOG.warn("Failed resolve " + isa);<a name="line.282"></a>
-<span class="sourceLineNo">283</span> }<a name="line.283"></a>
-<span class="sourceLineNo">284</span> InetAddress regionAddress = isa.getAddress();<a name="line.284"></a>
-<span class="sourceLineNo">285</span> String regionLocation;<a name="line.285"></a>
-<span class="sourceLineNo">286</span> regionLocation = reverseDNS(regionAddress);<a name="line.286"></a>
-<span class="sourceLineNo">287</span> <a name="line.287"></a>
-<span class="sourceLineNo">288</span> byte[] startRow = scan.getStartRow();<a name="line.288"></a>
-<span class="sourceLineNo">289</span> byte[] stopRow = scan.getStopRow();<a name="line.289"></a>
-<span class="sourceLineNo">290</span> // determine if the given start an stop key fall into the region<a name="line.290"></a>
-<span class="sourceLineNo">291</span> if ((startRow.length == 0 || keys.getSecond()[i].length == 0 ||<a name="line.291"></a>
-<span class="sourceLineNo">292</span> Bytes.compareTo(startRow, keys.getSecond()[i]) < 0) &&<a name="line.292"></a>
-<span class="sourceLineNo">293</span> (stopRow.length == 0 ||<a name="line.293"></a>
-<span class="sourceLineNo">294</span> Bytes.compareTo(stopRow, keys.getFirst()[i]) > 0)) {<a name="line.294"></a>
-<span class="sourceLineNo">295</span> byte[] splitStart = startRow.length == 0 ||<a name="line.295"></a>
-<span class="sourceLineNo">296</span> Bytes.compareTo(keys.getFirst()[i], startRow) >= 0 ?<a name="line.296"></a>
-<span class="sourceLineNo">297</span> keys.getFirst()[i] : startRow;<a name="line.297"></a>
-<span class="sourceLineNo">298</span> byte[] splitStop = (stopRow.length == 0 ||<a name="line.298"></a>
-<span class="sourceLineNo">299</span> Bytes.compareTo(keys.getSecond()[i], stopRow) <= 0) &&<a name="line.299"></a>
-<span class="sourceLineNo">300</span> keys.getSecond()[i].length > 0 ?<a name="line.300"></a>
-<span class="sourceLineNo">301</span> keys.getSecond()[i] : stopRow;<a name="line.301"></a>
-<span class="sourceLineNo">302</span> <a name="line.302"></a>
-<span class="sourceLineNo">303</span> byte[] regionName = location.getRegionInfo().getRegionName();<a name="line.303"></a>
-<span class="sourceLineNo">304</span> String encodedRegionName = location.getRegionInfo().getEncodedName();<a name="line.304"></a>
-<span class="sourceLineNo">305</span> long regionSize = sizeCalculator.getRegionSize(regionName);<a name="line.305"></a>
-<span class="sourceLineNo">306</span> TableSplit split = new TableSplit(tableName, scan,<a name="line.306"></a>
-<span class="sourceLineNo">307</span> splitStart, splitStop, regionLocation, encodedRegionName, regionSize);<a name="line.307"></a>
-<span class="sourceLineNo">308</span> splits.add(split);<a name="line.308"></a>
-<span class="sourceLineNo">309</span> if (LOG.isDebugEnabled()) {<a name="line.309"></a>
-<span class="sourceLineNo">310</span> LOG.debug("getSplits: split -> " + i + " -> " + split);<a name="line.310"></a>
-<span class="sourceLineNo">311</span> }<a name="line.311"></a>
-<span class="sourceLineNo">312</span> }<a name="line.312"></a>
-<span class="sourceLineNo">313</span> }<a name="line.313"></a>
-<span class="sourceLineNo">314</span> //The default value of "hbase.mapreduce.input.autobalance" is false, which means not enabled.<a name="line.314"></a>
-<span class="sourceLineNo">315</span> boolean enableAutoBalance = context.getConfiguration()<a name="line.315"></a>
-<span class="sourceLineNo">316</span> .getBoolean(MAPREDUCE_INPUT_AUTOBALANCE, false);<a name="line.316"></a>
-<span class="sourceLineNo">317</span> if (enableAutoBalance) {<a name="line.317"></a>
-<span class="sourceLineNo">318</span> long totalRegionSize=0;<a name="line.318"></a>
-<span class="sourceLineNo">319</span> for (int i = 0; i < splits.size(); i++){<a name="line.319"></a>
-<span class="sourceLineNo">320</span> TableSplit ts = (TableSplit)splits.get(i);<a name="line.320"></a>
-<span class="sourceLineNo">321</span> totalRegionSize += ts.getLength();<a name="line.321"></a>
-<span class="sourceLineNo">322</span> }<a name="line.322"></a>
-<span class="sourceLineNo">323</span> long averageRegionSize = totalRegionSize / splits.size();<a name="line.323"></a>
-<span class="sourceLineNo">324</span> // the averageRegionSize must be positive.<a name="line.324"></a>
-<span class="sourceLineNo">325</span> if (averageRegionSize <= 0) {<a name="line.325"></a>
-<span class="sourceLineNo">326</span> LOG.warn("The averageRegionSize is not positive: "+ averageRegionSize + ", " +<a name="line.326"></a>
-<span class="sourceLineNo">327</span> "set it to 1.");<a name="line.327"></a>
-<span class="sourceLineNo">328</span> averageRegionSize = 1;<a name="line.328"></a>
-<span class="sourceLineNo">329</span> }<a name="line.329"></a>
-<span class="sourceLineNo">330</span> return calculateRebalancedSplits(splits, context, averageRegionSize);<a name="line.330"></a>
-<span class="sourceLineNo">331</span> } else {<a name="line.331"></a>
-<span class="sourceLineNo">332</span> return splits;<a name="line.332"></a>
-<span class="sourceLineNo">333</span> }<a name="line.333"></a>
-<span class="sourceLineNo">334</span> } finally {<a name="line.334"></a>
-<span class="sourceLineNo">335</span> if (closeOnFinish) {<a name="line.335"></a>
-<span class="sourceLineNo">336</span> closeTable();<a name="line.336"></a>
-<span class="sourceLineNo">337</span> }<a name="line.337"></a>
-<span class="sourceLineNo">338</span> }<a name="line.338"></a>
-<span class="sourceLineNo">339</span> }<a name="line.339"></a>
-<span class="sourceLineNo">340</span><a name="line.340"></a>
-<span class="sourceLineNo">341</span> String reverseDNS(InetAddress ipAddress) throws UnknownHostException {<a name="line.341"></a>
-<span class="sourceLineNo">342</span> String hostName = this.reverseDNSCacheMap.get(ipAddress);<a name="line.342"></a>
-<span class="sourceLineNo">343</span> if (hostName == null) {<a name="line.343"></a>
-<span class="sourceLineNo">344</span> String ipAddressString = null;<a name="line.344"></a>
-<span class="sourceLineNo">345</span> try {<a name="line.345"></a>
-<span class="sourceLineNo">346</span> ipAddressString = DNS.reverseDns(ipAddress, null);<a name="line.346"></a>
-<span class="sourceLineNo">347</span> } catch (Exception e) {<a name="line.347"></a>
-<span class="sourceLineNo">348</span> // We can use InetAddress in case the jndi failed to pull up the reverse DNS entry from the<a name="line.348"></a>
-<span class="sourceLineNo">349</span> // name service. Also, in case of ipv6, we need to use the InetAddress since resolving<a name="line.349"></a>
-<span class="sourceLineNo">350</span> // reverse DNS using jndi doesn't work well with ipv6 addresses.<a name="line.350"></a>
-<span class="sourceLineNo">351</span> ipAddressString = InetAddress.getByName(ipAddress.getHostAddress()).getHostName();<a name="line.351"></a>
-<span class="sourceLineNo">352</span> }<a name="line.352"></a>
-<span class="sourceLineNo">353</span> if (ipAddressString == null) throw new UnknownHostException("No host found for " + ipAddress);<a name="line.353"></a>
-<span class="sourceLineNo">354</span> hostName = Strings.domainNamePointerToHostName(ipAddressString);<a name="line.354"></a>
-<span class="sourceLineNo">355</span> this.reverseDNSCacheMap.put(ipAddress, hostName);<a name="line.355"></a>
-<span class="sourceLineNo">356</span> }<a name="line.356"></a>
-<span class="sourceLineNo">357</span> return hostName;<a name="line.357"></a>
-<span class="sourceLineNo">358</span> }<a name="line.358"></a>
-<span class="sourceLineNo">359</span><a name="line.359"></a>
-<span class="sourceLineNo">360</span> /**<a name="line.360"></a>
-<span class="sourceLineNo">361</span> * Calculates the number of MapReduce input splits for the map tasks. The number of<a name="line.361"></a>
-<span class="sourceLineNo">362</span> * MapReduce input splits depends on the average region size and the "data skew ratio" user set in<a name="line.362"></a>
-<span class="sourceLineNo">363</span> * configuration.<a name="line.363"></a>
-<span class="sourceLineNo">364</span> *<a name="line.364"></a>
-<span class="sourceLineNo">365</span> * @param list The list of input splits before balance.<a name="line.365"></a>
-<span class="sourceLineNo">366</span> * @param context The current job context.<a name="line.366"></a>
-<span class="sourceLineNo">367</span> * @param average The average size of all regions .<a name="line.367"></a>
-<span class="sourceLineNo">368</span> * @return The list of input splits.<a name="line.368"></a>
-<span class="sourceLineNo">369</span> * @throws IOException When creating the list of splits fails.<a name="line.369"></a>
-<span class="sourceLineNo">370</span> * @see org.apache.hadoop.mapreduce.InputFormat#getSplits(<a name="line.370"></a>
-<span class="sourceLineNo">371</span> * org.apache.hadoop.mapreduce.JobContext)<a name="line.371"></a>
-<span class="sourceLineNo">372</span> */<a name="line.372"></a>
-<span class="sourceLineNo">373</span> private List<InputSplit> calculateRebalancedSplits(List<InputSplit> list, JobContext context,<a name="line.373"></a>
-<span class="sourceLineNo">374</span> long average) throws IOException {<a name="line.374"></a>
-<span class="sourceLineNo">375</span> List<InputSplit> resultList = new ArrayList<InputSplit>();<a name="line.375"></a>
-<span class="sourceLineNo">376</span> Configuration conf = context.getConfiguration();<a name="line.376"></a>
-<span class="sourceLineNo">377</span> //The default data skew ratio is 3<a name="line.377"></a>
-<span class="sourceLineNo">378</span> long dataSkewRatio = conf.getLong(INPUT_AUTOBALANCE_MAXSKEWRATIO, 3);<a name="line.378"></a>
-<span class="sourceLineNo">379</span> //It determines which mode to use: text key mode or binary key mode. The default is text mode.<a name="line.379"></a>
-<span class="sourceLineNo">380</span> boolean isTextKey = context.getConfiguration().getBoolean(TABLE_ROW_TEXTKEY, true);<a name="line.380"></a>
-<span class="sourceLineNo">381</span> long dataSkewThreshold = dataSkewRatio * average;<a name="line.381"></a>
-<span class="sourceLineNo">382</span> int count = 0;<a name="line.382"></a>
-<span class="sourceLineNo">383</span> while (count < list.size()) {<a name="line.383"></a>
-<span class="sourceLineNo">384</span> TableSplit ts = (TableSplit)list.get(count);<a name="line.384"></a>
-<span class="sourceLineNo">385</span> TableName tableName = ts.getTable();<a name="line.385"></a>
-<span class="sourceLineNo">386</span> String regionLocation = ts.getRegionLocation();<a name="line.386"></a>
-<span class="sourceLineNo">387</span> String encodedRegionName = ts.getEncodedRegionName();<a name="line.387"></a>
-<span class="sourceLineNo">388</span> long regionSize = ts.getLength();<a name="line.388"></a>
-<span class="sourceLineNo">389</span> if (regionSize >= dataSkewThreshold) {<a name="line.389"></a>
-<span class="sourceLineNo">390</span> // if the current region size is large than the data skew threshold,<a name="line.390"></a>
-<span class="sourceLineNo">391</span> // split the region into two MapReduce input splits.<a name="line.391"></a>
-<span class="sourceLineNo">392</span> byte[] splitKey = getSplitKey(ts.getStartRow(), ts.getEndRow(), isTextKey);<a name="line.392"></a>
-<span class="sourceLineNo">393</span> if (Arrays.equals(ts.getEndRow(), splitKey)) {<a name="line.393"></a>
-<span class="sourceLineNo">394</span> // Not splitting since the end key is the same as the split key<a name="line.394"></a>
-<span class="sourceLineNo">395</span> resultList.add(ts);<a name="line.395"></a>
-<span class="sourceLineNo">396</span> } else {<a name="line.396"></a>
-<span class="sourceLineNo">397</span> //Set the size of child TableSplit as 1/2 of the region size. The exact size of the<a name="line.397"></a>
-<span class="sourceLineNo">398</span> // MapReduce input splits is not far off.<a name="line.398"></a>
-<span class="sourceLineNo">399</span> TableSplit t1 = new TableSplit(tableName, scan, ts.getStartRow(), splitKey,<a name="line.399"></a>
-<span class="sourceLineNo">400</span> regionLocation, regionSize / 2);<a name="line.400"></a>
-<span class="sourceLineNo">401</span> TableSplit t2 = new TableSplit(tableName, scan, splitKey, ts.getEndRow(), regionLocation,<a name="line.401"></a>
-<span class="sourceLineNo">402</span> regionSize - regionSize / 2);<a name="line.402"></a>
-<span class="sourceLineNo">403</span> resultList.add(t1);<a name="line.403"></a>
-<span class="sourceLineNo">404</span> resultList.add(t2);<a name="line.404"></a>
-<span class="sourceLineNo">405</span> }<a name="line.405"></a>
-<span class="sourceLineNo">406</span> count++;<a name="line.406"></a>
-<span class="sourceLineNo">407</span> } else if (regionSize >= average) {<a name="line.407"></a>
-<span class="sourceLineNo">408</span> // if the region size between average size and data skew threshold size,<a name="line.408"></a>
-<span class="sourceLineNo">409</span> // make this region as one MapReduce input split.<a name="line.409"></a>
-<span class="sourceLineNo">410</span> resultList.add(ts);<a name="line.410"></a>
-<span class="sourceLineNo">411</span> count++;<a name="line.411"></a>
-<span class="sourceLineNo">412</span> } else {<a name="line.412"></a>
-<span class="sourceLineNo">413</span> // if the total size of several small continuous regions less than the average region size,<a name="line.413"></a>
-<span class="sourceLineNo">414</span> // combine them into one MapReduce input split.<a name="line.414"></a>
-<span class="sourceLineNo">415</span> long totalSize = regionSize;<a name="line.415"></a>
-<span class="sourceLineNo">416</span> byte[] splitStartKey = ts.getStartRow();<a name="line.416"></a>
-<span class="sourceLineNo">417</span> byte[] splitEndKey = ts.getEndRow();<a name="line.417"></a>
-<span class="sourceLineNo">418</span> count++;<a name="line.418"></a>
-<span class="sourceLineNo">419</span> for (; count < list.size(); count++) {<a name="line.419"></a>
-<span class="sourceLineNo">420</span> TableSplit nextRegion = (TableSplit)list.get(count);<a name="line.420"></a>
-<span class="sourceLineNo">421</span> long nextRegionSize = nextRegion.getLength();<a name="line.421"></a>
-<span class="sourceLineNo">422</span> if (totalSize + nextRegionSize <= dataSkewThreshold) {<a name="line.422"></a>
-<span class="sourceLineNo">423</span> totalSize = totalSize + nextRegionSize;<a name="line.423"></a>
-<span class="sourceLineNo">424</span> splitEndKey = nextRegion.getEndRow();<a name="line.424"></a>
-<span class="sourceLineNo">425</span> } else {<a name="line.425"></a>
-<span class="sourceLineNo">426</span> break;<a name="line.426"></a>
-<span class="sourceLineNo">427</span> }<a name="line.427"></a>
-<span class="sourceLineNo">428</span> }<a name="line.428"></a>
-<span class="sourceLineNo">429</span> TableSplit t = new TableSplit(tableName, scan, splitStartKey, splitEndKey,<a name="line.429"></a>
-<span class="sourceLineNo">430</span> regionLocation, encodedRegionName, totalSize);<a name="line.430"></a>
-<span class="sourceLineNo">431</span> resultList.add(t);<a name="line.431"></a>
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-<span class="sourceLineNo">433</span> }<a name="line.433"></a>
-<span class="sourceLineNo">434</span> return resultList;<a name="line.434"></a>
-<span class="sourceLineNo">435</span> }<a name="line.435"></a>
-<span class="sourceLineNo">436</span><a name="line.436"></a>
-<span class="sourceLineNo">437</span> /**<a name="line.437"></a>
-<span class="sourceLineNo">438</span> * select a split point in the region. The selection of the split point is based on an uniform<a name="line.438"></a>
-<span class="sourceLineNo">439</span> * distribution assumption for the keys in a region.<a name="line.439"></a>
-<span class="sourceLineNo">440</span> * Here are some examples:<a name="line.440"></a>
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-<span class="sourceLineNo">444</span> * <th>start key</th><a name="line.444"></a>
-<span class="sourceLineNo">445</span> * <th>end key</th><a name="line.445"></a>
-<span class="sourceLineNo">446</span> * <th>is text</th><a name="line.446"></a>
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-<span class="sourceLineNo">449</span> * <tr><a name="line.449"></a>
-<span class="sourceLineNo">450</span> * <td>'a', 'a', 'a', 'b', 'c', 'd', 'e', 'f', 'g'</td><a name="line.450"></a>
-<span class="sourceLineNo">451</span> * <td>'a', 'a', 'a', 'f', 'f', 'f'</td><a name="line.451"></a>
-<span class="sourceLineNo">452</span> * <td>true</td><a name="line.452"></a>
-<span class="sourceLineNo">453</span> * <td>'a', 'a', 'a', 'd', 'd', -78, 50, -77, 51</td><a name="line.453"></a>
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-<span class="sourceLineNo">455</span> * <tr><a name="line.455"></a>
-<span class="sourceLineNo">456</span> * <td>'1', '1', '1', '0', '0', '0'</td><a name="line.456"></a>
-<span class="sourceLineNo">457</span> * <td>'1', '1', '2', '5', '7', '9', '0'</td><a name="line.457"></a>
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-<span class="sourceLineNo">459</span> * <td>'1', '1', '1', -78, -77, -76, -104</td><a name="line.459"></a>
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-<span class="sourceLineNo">463</span> * <td>'1', '1', '2', '0'</td><a name="line.463"></a>
-<span class="sourceLineNo">464</span> * <td>true</td><a name="line.464"></a>
-<span class="sourceLineNo">465</span> * <td>'1', '1', '1', -80</td><a name="line.465"></a>
-<span class="sourceLineNo">466</span> * </tr><a name="line.466"></a>
-<span class="sourceLineNo">467</span> * <tr><a name="line.467"></a>
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-<span class="sourceLineNo">469</span> * <td>13, -19, 127, 0</td><a name="line.469"></a>
-<span class="sourceLineNo">470</span> * <td>false</td><a name="line.470"></a>
-<span class="sourceLineNo">471</span> * <td>13, -19, 126, -65</td><a name="line.471"></a>
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-<span class="sourceLineNo">473</span> * </table><a name="line.473"></a>
-<span class="sourceLineNo">474</span> *<a name="line.474"></a>
-<span class="sourceLineNo">475</span> * Set this function as "public static", make it easier for test.<a name="line.475"></a>
-<span class="sourceLineNo">476</span> *<a name="line.476"></a>
-<span class="sourceLineNo">477</span> * @param start Start key of the region<a name="line.477"></a>
-<span class="sourceLineNo">478</span> * @param end End key of the region<a name="line.478"></a>
-<span class="sourceLineNo">479</span> * @param isText It determines to use text key mode or binary key mode<a name="line.479"></a>
-<span class="sourceLineNo">480</span> * @return The split point in the region.<a name="line.480"></a>
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-<span class="sourceLineNo">482</span> @InterfaceAudience.Private<a name="line.482"></a>
-<span class="sourceLineNo">483</span> public static byte[] getSplitKey(byte[] start, byte[] end, boolean isText) {<a name="line.483"></a>
-<span class="sourceLineNo">484</span> byte upperLimitByte;<a name="line.484"></a>
-<span class="sourceLineNo">485</span> byte lowerLimitByte;<a name="line.485"></a>
-<span class="sourceLineNo">486</span> //Use text mode or binary mode.<a name="line.486"></a>
-<span class="sourceLineNo">487</span> if (isText) {<a name="line.487"></a>
-<span class="sourceLineNo">488</span> //The range of text char set in ASCII is [32,126], the lower limit is space and the upper<a name="line.488"></a>
-<span class="sourceLineNo">489</span> // limit is '~'.<a name="line.489"></a>
-<span class="sourceLineNo">490</span> upperLimitByte = '~';<a name="line.490"></a>
-<span class="sourceLineNo">491</span> lowerLimitByte = ' ';<a name="line.491"></a>
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-<span class="sourceLineNo">493</span> upperLimitByte = -1;<a name="line.493"></a>
-<span class="sourceLineNo">494</span> lowerLimitByte = 0;<a name="line.494"></a>
-<span class="sourceLineNo">495</span> }<a name="line.495"></a>
-<span class="sourceLineNo">496</span> // For special case<a name="line.496"></a>
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-<span class="sourceLineNo">498</span> // Example 2 (text key mode): startKey="ffffaaa", endKey=null, splitkey="f~~~~~~"<a name="line.498"></a>
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+<span class="sourceLineNo">293</span><a name="line.293"></a>
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+<span class="sourceLineNo">306</span> long regionSize = sizeCalculator.getRegionSize(regionName);<a name="line.306"></a>
+<span class="sourceLineNo">307</span> TableSplit split = new TableSplit(tableName, scan,<a name="line.307"></a>
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+<span class="sourceLineNo">361</span> /**<a name="line.361"></a>
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+<span class="sourceLineNo">372</span> * org.apache.hadoop.mapreduce.JobContext)<a name="line.372"></a>
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+<span class="sourceLineNo">378</span> //The default data skew ratio is 3<a name="line.378"></a>
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+<span class="sourceLineNo">419</span> count++;<a name="line.419"></a>
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