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| Minor Fragment ID | Host Name | Start | End | Runtime | Max Records | Max Batches | Last Update | Last Progress | Peak Memory | State | | 05-00-xx | bigdata2 | 1.529s | 24m46s | 24m45s | 71,555,857 | 21,985 | 12:16:02 | 12:16:02 | 7.68GB | CANCELLATION_REQUESTED | | 05-01-xx | bigdata4 | 1.566s | 24m47s | 24m45s | 71,567,860 | 21,990 | 12:16:02 | 12:16:02 | 7.69GB | CANCELLATION_REQUESTED | | 05-02-xx | bigdata3 | 1.526s | 22m15s | 22m13s | 71,551,338 | 21,981 | 12:13:30 | 12:13:25 | 7.68GB | RUNNING | | 05-03-xx | bigdata2 | 1.530s | 25m16s | 25m15s | 71,565,965 | 21,982 | 12:16:32 | 12:16:32 | 7.70GB | CANCELLATION_REQUESTED | | 05-04-xx | bigdata4 | 1.567s | 25m17s | 25m15s | 71,556,216 | 21,988 | 12:16:32 | 12:16:32 | 7.70GB | CANCELLATION_REQUESTED | | 05-05-xx | bigdata3 | 1.527s | 22m15s | 22m13s | 71,550,821 | 21,983 | 12:13:30 | 12:13:25 | 7.68GB | RUNNING | | 05-06-xx | bigdata2 | 1.531s | 25m46s | 25m45s | 71,558,873 | 21,983 | 12:17:02 | 12:17:02 | 7.70GB | CANCELLATION_REQUESTED | | 05-07-xx | bigdata4 | 1.568s | 25m47s | 25m45s | 71,558,657 | 21,982 | 12:17:02 | 12:17:02 | 7.67GB | CANCELLATION_REQUESTED | | 05-08-xx | bigdata3 | 1.528s | 22m15s | 22m13s | 71,558,109 | 21,989 | 12:13:30 | 12:13:25 | 7.69GB | RUNNING | | 05-09-xx | bigdata2 | 1.532s | 26m17s | 26m15s | 71,558,226 | 21,983 | 12:17:32 | 12:17:32 | 7.68GB | CANCELLATION_REQUESTED | | 05-10-xx | bigdata4 | 1.568s | 26m17s | 26m15s | 71,558,359 | 21,980 | 12:17:32 | 12:17:32 | 7.68GB | CANCELLATION_REQUESTED | | 05-11-xx | bigdata3 | 1.529s | 22m15s | 22m13s | 71,537,409 | 21,975 | 12:13:30 | 12:13:30 | 7.69GB | RUNNING | | 05-12-xx | bigdata2 | 1.533s | 26m47s | 26m45s | 71,037,058 | 21,800 | 12:18:02 | 12:18:02 | 7.63GB | CANCELLATION_REQUESTED | | 05-13-xx | bigdata4 | 1.569s | 26m47s | 26m45s | 71,040,788 | 21,805 | 12:18:02 | 12:18:02 | 7.64GB | CANCELLATION_REQUESTED | | 05-14-xx | bigdata3 | 1.529s | 22m15s | 22m13s | 71,001,401 | 21,791 | 12:13:30 | 12:13:25 | 7.65GB | RUNNING | | 05-15-xx | bigdata2 | 1.533s | 27m17s | 27m15s | 71,007,623 | 21,793 | 12:18:32 | 12:18:32 | 7.62GB | CANCELLATION_REQUESTED | | 05-16-xx | bigdata4 | 1.570s | 27m17s | 27m15s | 71,029,560 | 21,793 | 12:18:32 | 12:18:32 | 7.63GB | CANCELLATION_REQUESTED | | 05-17-xx | bigdata3 | 1.530s | 22m15s | 22m13s | 71,057,938 | 21,806 | 12:13:30 | 12:13:30 | 7.64GB | RUNNING | -- thanks for your regards. At 2016-05-10 15:01:14, "leezy" <[email protected]> wrote: here is the failure profiles. And i see the memory is not exceed 55G in each node. -- thanks for your regards. At 2016-05-10 14:47:10, "leezy" <[email protected]> wrote: >Leon,thank you for your reply, yes, i have set the driver memory to 55G and >the java heap memory to 8G. And this user case is run successfully in the >impala that installed on the same cluster. But in drill , the cmd always show >the follow errors: >Error: RESOURCE ERROR: One or more nodes ran out of memory while executing the >query. > >Failure allocating buffer. >Fragment 3:6 > >[Error Id: d623b6b2-279d-4d24-af4d-0b62554b440c on bigdata2:31010] >(state=,code=0) > > >i think i miss some configuration. > > > > >-- > > >thanks for your regards. > > > > >At 2016-05-10 13:51:12, "Leon Clayton" <[email protected]> wrote: >>did you increase the memory setting for Drill from the default? >> >>https://drill.apache.org/docs/configuring-drill-memory/ >><https://drill.apache.org/docs/configuring-drill-memory/> >> >> >>> On 10 May 2016, at 02:25, [email protected] wrote: >>> >>> >>> hi: >>> i run join operation in the drill, i use broadcast and put the small table >>> in the right. The small table has 32000000 rows. I have set the >>> planner.broadcast_threshold to 100000000. The cluster has three nodes and >>> every node has 64G memory. when join is running, the memory is increasing >>> untill the driilbit process exit. But the same query is run successful in >>> the impala and they are in the same cluster. >>> here is the query plan. >>> >>> 00-00 Screen : rowType = RecordType(VARCHAR(65535) sourceIP, DOUBLE >>> totalRevenue, ANY avgPageRank): rowcount = 1.0, cumulative cost = >>> {5.294005617599999E8 rows, 6.356723058846001E10 cpu, 0.0 io, >>> 1.4803953770495996E11 network, 9.1066982688E8 memory}, id = 5015 >>> 00-01 Project(sourceIP=[$0], totalRevenue=[$1], avgPageRank=[$2]) : >>> rowType = RecordType(VARCHAR(65535) sourceIP, DOUBLE totalRevenue, ANY >>> avgPageRank): rowcount = 1.0, cumulative cost = {5.2940056165999985E8 rows, >>> 6.356723058836001E10 cpu, 0.0 io, 1.4803953770495996E11 network, >>> 9.1066982688E8 memory}, id = 5014 >>> 00-02 SelectionVectorRemover : rowType = RecordType(VARCHAR(65535) >>> sourceIP, DOUBLE totalRevenue, ANY avgPageRank): rowcount = 1.0, cumulative >>> cost = {5.2940056165999985E8 rows, 6.356723058836001E10 cpu, 0.0 io, >>> 1.4803953770495996E11 network, 9.1066982688E8 memory}, id = 5013 >>> 00-03 Limit(fetch=[1]) : rowType = RecordType(VARCHAR(65535) >>> sourceIP, DOUBLE totalRevenue, ANY avgPageRank): rowcount = 1.0, cumulative >>> cost = {5.2940056065999985E8 rows, 6.356723058736001E10 cpu, 0.0 io, >>> 1.4803953770495996E11 network, 9.1066982688E8 memory}, id = 5012 >>> 00-04 SingleMergeExchange(sort0=[1 DESC]) : rowType = >>> RecordType(VARCHAR(65535) sourceIP, DOUBLE totalRevenue, ANY avgPageRank): >>> rowcount = 457983.77999999997, cumulative cost = {5.2940055965999985E8 >>> rows, 6.356723058336001E10 cpu, 0.0 io, 1.4803953770495996E11 network, >>> 9.1066982688E8 memory}, id = 5011 >>> 01-01 SelectionVectorRemover : rowType = >>> RecordType(VARCHAR(65535) sourceIP, DOUBLE totalRevenue, ANY avgPageRank): >>> rowcount = 457983.77999999997, cumulative cost = {5.289425758799999E8 rows, >>> 6.356173477800001E10 cpu, 0.0 io, 1.4241183301631998E11 network, >>> 9.1066982688E8 memory}, id = 5010 >>> 01-02 TopN(limit=[1]) : rowType = RecordType(VARCHAR(65535) >>> sourceIP, DOUBLE totalRevenue, ANY avgPageRank): rowcount = >>> 457983.77999999997, cumulative cost = {5.284845920999999E8 rows, >>> 6.356127679422001E10 cpu, 0.0 io, 1.4241183301631998E11 network, >>> 9.1066982688E8 memory}, id = 5009 >>> 01-03 Project(sourceIP=[$0], totalRevenue=[$1], >>> avgPageRank=[$2]) : rowType = RecordType(VARCHAR(65535) sourceIP, DOUBLE >>> totalRevenue, ANY avgPageRank): rowcount = 457983.77999999997, cumulative >>> cost = {5.2802660831999993E8 rows, 6.356127679422001E10 cpu, 0.0 io, >>> 1.4241183301631998E11 network, 9.1066982688E8 memory}, id = 5008 >>> 01-04 HashToRandomExchange(dist0=[[$1]]) : rowType = >>> RecordType(VARCHAR(65535) sourceIP, DOUBLE totalRevenue, ANY avgPageRank, >>> ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount = 457983.77999999997, cumulative >>> cost = {5.2802660831999993E8 rows, 6.356127679422001E10 cpu, 0.0 io, >>> 1.4241183301631998E11 network, 9.1066982688E8 memory}, id = 5007 >>> 02-01 UnorderedMuxExchange : rowType = >>> RecordType(VARCHAR(65535) sourceIP, DOUBLE totalRevenue, ANY avgPageRank, >>> ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount = 457983.77999999997, cumulative >>> cost = {5.2756862453999996E8 rows, 6.3553949053740005E10 cpu, 0.0 io, >>> 1.3490822676479999E11 network, 9.1066982688E8 memory}, id = 5006 >>> 03-01 Project(sourceIP=[$0], totalRevenue=[$1], >>> avgPageRank=[$2], E_X_P_R_H_A_S_H_F_I_E_L_D=[hash32AsDouble($1)]) : rowType >>> = RecordType(VARCHAR(65535) sourceIP, DOUBLE totalRevenue, ANY avgPageRank, >>> ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount = 457983.77999999997, cumulative >>> cost = {5.2711064076E8 rows, 6.355349106996001E10 cpu, 0.0 io, >>> 1.3490822676479999E11 network, 9.1066982688E8 memory}, id = 5005 >>> 03-02 Project(sourceIP=[$0], >>> totalRevenue=[CASE(=($4, 0), null, $3)], >>> avgPageRank=[CAST(/(CastHigh(CASE(=($2, 0), null, $1)), $2)):ANY NOT NULL]) >>> : rowType = RecordType(VARCHAR(65535) sourceIP, DOUBLE totalRevenue, ANY >>> avgPageRank): rowcount = 457983.77999999997, cumulative cost = >>> {5.2665265698E8 rows, 6.3551659134840004E10 cpu, 0.0 io, >>> 1.3490822676479999E11 network, 9.1066982688E8 memory}, id = 5004 >>> 03-03 HashAgg(group=[{0}], agg#0=[$SUM0($1)], >>> agg#1=[$SUM0($2)], agg#2=[$SUM0($3)], agg#3=[$SUM0($4)]) : rowType = >>> RecordType(VARCHAR(65535) sourceIP, INTEGER $f1, BIGINT $f2, DOUBLE $f3, >>> BIGINT $f4): rowcount = 457983.77999999997, cumulative cost = >>> {5.2619467320000005E8 rows, 6.3547995264600006E10 cpu, 0.0 io, >>> 1.3490822676479999E11 network, 9.1066982688E8 memory}, id = 5003 >>> 03-04 Project(sourceIP=[$0], $f1=[$1], >>> $f2=[$2], $f3=[$3], $f4=[$4]) : rowType = RecordType(VARCHAR(65535) >>> sourceIP, INTEGER $f1, BIGINT $f2, DOUBLE $f3, BIGINT $f4): rowcount = >>> 4579837.8, cumulative cost = {5.2161483540000004E8 rows, 6.32915243478E10 >>> cpu, 0.0 io, 1.3490822676479999E11 network, 8.300646816E8 memory}, id = 5002 >>> 03-05 HashToRandomExchange(dist0=[[$0]]) : >>> rowType = RecordType(VARCHAR(65535) sourceIP, INTEGER $f1, BIGINT $f2, >>> DOUBLE $f3, BIGINT $f4, ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount = >>> 4579837.8, cumulative cost = {5.2161483540000004E8 rows, 6.32915243478E10 >>> cpu, 0.0 io, 1.3490822676479999E11 network, 8.300646816E8 memory}, id = 5001 >>> 04-01 UnorderedMuxExchange : rowType = >>> RecordType(VARCHAR(65535) sourceIP, INTEGER $f1, BIGINT $f2, DOUBLE $f3, >>> BIGINT $f4, ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount = 4579837.8, >>> cumulative cost = {5.170349976E8 rows, 6.3218246943E10 cpu, 0.0 io, >>> 2.2354132992E10 network, 8.300646816E8 memory}, id = 5000 >>> 05-01 Project(sourceIP=[$0], $f1=[$1], >>> $f2=[$2], $f3=[$3], $f4=[$4], >>> E_X_P_R_H_A_S_H_F_I_E_L_D=[hash32AsDouble($0)]) : rowType = >>> RecordType(VARCHAR(65535) sourceIP, INTEGER $f1, BIGINT $f2, DOUBLE $f3, >>> BIGINT $f4, ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount = 4579837.8, >>> cumulative cost = {5.124551598E8 rows, 6.32136671052E10 cpu, 0.0 io, >>> 2.2354132992E10 network, 8.300646816E8 memory}, id = 4999 >>> 05-02 HashAgg(group=[{0}], >>> agg#0=[$SUM0($1)], agg#1=[COUNT($1)], agg#2=[$SUM0($2)], agg#3=[COUNT($2)]) >>> : rowType = RecordType(VARCHAR(65535) sourceIP, INTEGER $f1, BIGINT $f2, >>> DOUBLE $f3, BIGINT $f4): rowcount = 4579837.8, cumulative cost = >>> {5.07875322E8 rows, 6.3195347754E10 cpu, 0.0 io, 2.2354132992E10 network, >>> 8.300646816E8 memory}, id = 4998 >>> 05-03 Project(sourceIP=[$0], >>> pagerank=[$5], adrevenue=[$3]) : rowType = RecordType(VARCHAR(65535) >>> sourceIP, INTEGER pagerank, DOUBLE adrevenue): rowcount = 4.5798378E7, >>> cumulative cost = {4.62076944E8 rows, 6.0630638586E10 cpu, 0.0 io, >>> 2.2354132992E10 network, 2.40132288E7 memory}, id = 4997 >>> 05-04 HashJoin(condition=[=($4, >>> $1)], joinType=[inner]) : rowType = RecordType(VARCHAR(65535) sourceip, >>> VARCHAR(65535) desturl, VARCHAR(65535) visitdate, DOUBLE adrevenue, >>> VARCHAR(65535) pageurl, INTEGER pagerank): rowcount = 4.5798378E7, >>> cumulative cost = {4.62076944E8 rows, 6.0630638586E10 cpu, 0.0 io, >>> 2.2354132992E10 network, 2.40132288E7 memory}, id = 4996 >>> 05-06 SelectionVectorRemover : >>> rowType = RecordType(VARCHAR(65535) sourceip, VARCHAR(65535) desturl, >>> VARCHAR(65535) visitdate, DOUBLE adrevenue): rowcount = 4.5798378E7, >>> cumulative cost = {4.12185402E8 rows, 5.9950076802E10 cpu, 0.0 io, 0.0 >>> network, 0.0 memory}, id = 4993 >>> 05-07 >>> Filter(condition=[AND(>=(DATEDIFF($2, '1980-01-01'), 0), <=(DATEDIFF($2, >>> '1980-04-01'), 0))]) : rowType = RecordType(VARCHAR(65535) sourceip, >>> VARCHAR(65535) desturl, VARCHAR(65535) visitdate, DOUBLE adrevenue): >>> rowcount = 4.5798378E7, cumulative cost = {3.66387024E8 rows, >>> 5.9904278424E10 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 4992 >>> 05-08 >>> Scan(groupscan=[HiveScan [table=Table(dbName:default, >>> tableName:uservisits_copy_huge), columns=[`sourceip`, `desturl`, >>> `visitdate`, `adrevenue`], numPartitions=0, partitions= null, >>> inputDirectories=[hdfs://nameservice1/HiBench/huge/Join/Input/uservisits]]]) >>> : rowType = RecordType(VARCHAR(65535) sourceip, VARCHAR(65535) desturl, >>> VARCHAR(65535) visitdate, DOUBLE adrevenue): rowcount = 1.83193512E8, >>> cumulative cost = {1.83193512E8 rows, 5.862192384E10 cpu, 0.0 io, 0.0 >>> network, 0.0 memory}, id = 4991 >>> 05-05 BroadcastExchange : >>> rowType = RecordType(VARCHAR(65535) pageurl, INTEGER pagerank): rowcount = >>> 1364388.0, cumulative cost = {2728776.0 rows, 1.20066144E8 cpu, 0.0 io, >>> 2.2354132992E10 network, 0.0 memory}, id = 4995 >>> 06-01 Scan(groupscan=[HiveScan >>> [table=Table(dbName:default, tableName:rankings_huge), columns=[`pageurl`, >>> `pagerank`], numPartitions=0, partitions= null, >>> inputDirectories=[hdfs://nameservice1/HiBench/huge/Join/Input/rankings]]]) >>> : rowType = RecordType(VARCHAR(65535) pageurl, INTEGER pagerank): rowcount >>> = 1364388.0, cumulative cost = {1364388.0 rows, 1.0915104E8 cpu, 0.0 io, >>> 0.0 network, 0.0 memory}, id = 4994 >>> -- >>> >>> thanks for your regards. >>> >>> >>> >>
