Bulk loader taking more than 100G virtual memory for 5.4G of data


(Himanshu Barthwal) #1

I am using dgraph bulk loader for loading json formatted data. Here is how my data directory looks like:

$ du -h ../dgraph_mutations/
5.4G    ../dgraph_mutations/

I am invoking bulk loader as follows:

$ dgraph bulk --zero=<somehost>:5080 --jsons=../dgraph_mutations/ --reduce_shards=1 --map_shards=1 --mapoutput_mb=1 --num_go_routines=1 --out=<some_directory> --schema_file=<partial_schema_file>

The above eventually leads to can't allocate memory error (most likely due to the ulimit imposed on the host as follows:

$ ulimit -v

The schema file is partial because I am just trying out dgraph and do not have the schema information before hand. So I just added a few predicates I know about. Also, I made map_shards=1 --mapoutput_mb=1 --num_go_routines=1 so that it uses less memory. But still, the virtual memory
usage peaks to ~104GB and Resident memory peaks at ~87G.
I was eventually able to get around this by using skip_map_phase and clean_temp options on the second attempt as the bulk loader was barely able to make it through map phase and was failing in the reduce phase in the first attempt. Here are my questions:

  1. Is this memory usage expected (even with the toned down flags) ?
  2. Is there any workaround for loading more data? I initially wanted to load around 11G of data but due OOM errors, I sliced my data into half and barely managed to load it.

(Michel Conrado) #2

Please share the log stamp that shows the version you are using.

(Manish R Jain) #3

This doesn’t look right at all. Can you take a heap profile and paste that here?


(Himanshu Barthwal) #4

@mrjn This time I tried running the bulk loader (on a r4.8xlarge EC2 instance) as follows:

$ dgraph bulk  --jsons=dgraph_mutations/ --reduce_shards=1 --map_shards=1 --schema_file=core_schema.txt --out=live --mapoutput_mb=1 --num_go_routines=4

Here is how my data directory looks like:

$ du -ch data/dgraph_mutations
14G     data/dgraph_mutations/dgraph_mutations
14G     data/dgraph_mutations
14G     total

After sometime it crashed as follows:

MAP 17m33s nquad_count:278.9M err_count:0.000 nquad_speed:264.8k/sec edge_count:613.4M edge_speed:582.5k/sec
MAP 17m34s nquad_count:279.1M err_count:0.000 nquad_speed:264.8k/sec edge_count:613.9M edge_speed:582.4k/sec
fatal error: runtime: cannot allocate memory
fatal error: runtime: cannot allocate memory
fatal error: runtime: cannot allocate memory
fatal error: runtime: cannot allocate memory

runtime stack:
runtime.throw(0x146eac0, 0x1f)
        /usr/local/go/src/runtime/panic.go:608 +0x72
        /usr/local/go/src/runtime/mheap.go:1668 +0xda
runtime.newMarkBits(0x33, 0x16)
        /usr/local/go/src/runtime/mheap.go:1588 +0xb3
runtime.heapBits.initSpan(0x7fa8a45bd200, 0x20317600000000, 0x7fa8a477ffff, 0x7fa4ade9f690)
        /usr/local/go/src/runtime/mbitmap.go:765 +0x74
runtime.(*mcentral).grow(0x1f7df38, 0x0)
        /usr/local/go/src/runtime/mcentral.go:240 +0x12a
runtime.(*mcentral).cacheSpan(0x1f7df38, 0x7fa4ade9f4c8)
        /usr/local/go/src/runtime/mcentral.go:106 +0x2f8
runtime.(*mcache).refill(0x7faa5efb3700, 0x7fa563534116)                                                      [361/1915]
        /usr/local/go/src/runtime/mcache.go:122 +0x95
        /usr/local/go/src/runtime/malloc.go:749 +0x32
        /usr/local/go/src/runtime/asm_amd64.s:351 +0x66

goroutine 381032 [running]:
        /usr/local/go/src/runtime/asm_amd64.s:311 fp=0xe164216b80 sp=0xe164216b78 pc=0x8d6450
runtime.(*mcache).nextFree(0x7faa5efb3700, 0xc5d879e416, 0x0, 0xca37462000, 0x1)
        /usr/local/go/src/runtime/malloc.go:748 +0xb6 fp=0xe164216bd8 sp=0xe164216b80 pc=0x886c96
runtime.mallocgc(0xa0, 0x1416680, 0x1, 0xc5d879e420)
        /usr/local/go/src/runtime/malloc.go:903 +0x793 fp=0xe164216c78 sp=0xe164216bd8 pc=0x8875e3
runtime.newobject(0x1416680, 0xf5e82c3979)
        /usr/local/go/src/runtime/malloc.go:1032 +0x38 fp=0xe164216ca8 sp=0xe164216c78 pc=0x8879c8
github.com/dgraph-io/dgraph/protos/pb.(*MapEntry).Unmarshal(0xc5d87993b0, 0xf5e82c3977, 0x2e, 0x28770e689, 0x1, 0x7fa563
        /ext-go/1/src/github.com/dgraph-io/dgraph/protos/pb/pb.pb.go:14783 +0x655 fp=0xe164216da0 sp=0xe164216ca8 pc=0xd
github.com/dgraph-io/dgraph/protos/pb.(*MapEntry).XXX_Unmarshal(0xc5d87993b0, 0xf5e82c3977, 0x2e, 0x28770e689, 0xc5d8799
3b0, 0xe164216e01)
        /ext-go/1/src/github.com/dgraph-io/dgraph/protos/pb/pb.pb.go:2835 +0x49 fp=0xe164216de0 sp=0xe164216da0 pc=0xcfb
github.com/dgraph-io/dgraph/vendor/github.com/gogo/protobuf/proto.Unmarshal(0xf5e82c3977, 0x2e, 0x28770e689, 0x1587ba0,
0xc5d87993b0, 0x0, 0x0)
        /ext-go/1/src/github.com/dgraph-io/dgraph/vendor/github.com/gogo/protobuf/proto/decode.go:338 +0x1c2 fp=0xe16421
6e48 sp=0xe164216de0 pc=0xfea322
github.com/dgraph-io/dgraph/dgraph/cmd/bulk.(*mapper).writeMapEntriesToFile(0xc0001b4940, 0xf50f9d2000, 0x220065a30, 0x3
60000000, 0x0)
        /ext-go/1/src/github.com/dgraph-io/dgraph/dgraph/cmd/bulk/mapper.go:89 +0x1b7 fp=0xe164216fb8 sp=0xe164216e48 pc
        /usr/local/go/src/runtime/asm_amd64.s:1333 +0x1 fp=0xe164216fc0 sp=0xe164216fb8 pc=0x8d8531           [326/1915]
created by github.com/dgraph-io/dgraph/dgraph/cmd/bulk.(*mapper).run
        /ext-go/1/src/github.com/dgraph-io/dgraph/dgraph/cmd/bulk/mapper.go:150 +0x258

goroutine 1 [semacquire, 14 minutes]:
        /usr/local/go/src/runtime/sema.go:56 +0x39
        /usr/local/go/src/sync/waitgroup.go:130 +0x64
        /ext-go/1/src/github.com/dgraph-io/dgraph/dgraph/cmd/bulk/loader.go:255 +0xa90
        /ext-go/1/src/github.com/dgraph-io/dgraph/dgraph/cmd/bulk/run.go:183 +0xb3f
github.com/dgraph-io/dgraph/dgraph/cmd/bulk.init.0.func1(0xc000103200, 0xc0001b8fc0, 0x0, 0x7)
        /ext-go/1/src/github.com/dgraph-io/dgraph/dgraph/cmd/bulk/run.go:44 +0x52
github.com/dgraph-io/dgraph/vendor/github.com/spf13/cobra.(*Command).execute(0xc000103200, 0xc0001b8e00, 0x7, 0x7, 0xc00
0103200, 0xc0001b8e00)
        /ext-go/1/src/github.com/dgraph-io/dgraph/vendor/github.com/spf13/cobra/command.go:702 +0x2d3
github.com/dgraph-io/dgraph/vendor/github.com/spf13/cobra.(*Command).ExecuteC(0x1ecd680, 0x8, 0x0, 0x0)
        /ext-go/1/src/github.com/dgraph-io/dgraph/vendor/github.com/spf13/cobra/command.go:783 +0x2dc
github.com/dgraph-io/dgraph/vendor/github.com/spf13/cobra.(*Command).Execute(0x1ecd680, 0x8ac98d, 0x1ed5868)
        /ext-go/1/src/github.com/dgraph-io/dgraph/vendor/github.com/spf13/cobra/command.go:736 +0x2b
        /ext-go/1/src/github.com/dgraph-io/dgraph/dgraph/cmd/root.go:58 +0x36
        /ext-go/1/src/github.com/dgraph-io/dgraph/dgraph/main.go:33 +0x88

goroutine 5 [chan receive]:
        /ext-go/1/src/github.com/dgraph-io/dgraph/vendor/github.com/golang/glog/glog.go:882 +0x8b
created by github.com/dgraph-io/dgraph/vendor/github.com/golang/glog.init.0
        /ext-go/1/src/github.com/dgraph-io/dgraph/vendor/github.com/golang/glog/glog.go:410 +0x203
goroutine 19 [syscall, 17 minutes]:
        /usr/local/go/src/runtime/sigqueue.go:139 +0x9c
        /usr/local/go/src/os/signal/signal_unix.go:23 +0x22
created by os/signal.init.0
        /usr/local/go/src/os/signal/signal_unix.go:29 +0x41

goroutine 20 [chan receive]:
        /ext-go/1/src/github.com/dgraph-io/dgraph/x/metrics.go:95 +0x7e
created by github.com/dgraph-io/dgraph/x.init.1
        /ext-go/1/src/github.com/dgraph-io/dgraph/x/metrics.go:90 +0x52c

goroutine 25 [select]:
        /go/src/go.opencensus.io/stats/view/worker.go:152 +0xdd
created by go.opencensus.io/stats/view.init.0
        /go/src/go.opencensus.io/stats/view/worker.go:29 +0x57

goroutine 26 [chan receive]:
        /ext-go/1/src/github.com/dgraph-io/dgraph/worker/proposal.go:61 +0x95
created by github.com/dgraph-io/dgraph/worker.init.0
        /ext-go/1/src/github.com/dgraph-io/dgraph/worker/proposal.go:46 +0x41

I am not pasting the whole stack trace above but hopefully the above is enough to give you an idea. Also, I took the heap profile (a few minutes before the crash) and here is how it looks like:

$ go tool pprof pprof.dgraph.alloc_objects.alloc_space.inuse_objects.inuse_space.004.pb
(pprof) top
Showing nodes accounting for 119.39GB, 98.64% of 121.04GB total
Dropped 104 nodes (cum <= 0.61GB)
Showing top 10 nodes out of 36
      flat  flat%   sum%        cum   cum%
   34.66GB 28.64% 28.64%    42.05GB 34.74%  github.com/dgraph-io/dgraph/edgraph.mapToNquads
   20.25GB 16.73% 45.37%    20.25GB 16.73%  github.com/dgraph-io/dgraph/x.ReserveCap
   17.14GB 14.16% 59.52%    18.06GB 14.92%  github.com/dgraph-io/dgraph/protos/pb.(*MapEntry).Unmarshal
      14GB 11.57% 71.09%       14GB 11.57%  bytes.makeSlice
   11.43GB  9.44% 80.53%    29.49GB 24.36%  github.com/dgraph-io/dgraph/dgraph/cmd/bulk.(*mapper).writeMapEntriesToF
    7.39GB  6.10% 86.64%     7.39GB  6.10%  github.com/dgraph-io/dgraph/edgraph.handleBasicType
    6.07GB  5.02% 91.65%    12.51GB 10.33%  encoding/json.(*decodeState).objectInterface
    5.82GB  4.81% 96.46%     5.82GB  4.81%  encoding/json.unquote
    1.71GB  1.41% 97.87%    56.57GB 46.74%  github.com/dgraph-io/dgraph/dgraph/cmd/bulk.jsonChunker.parse
    0.92GB  0.76% 98.64%     0.92GB  0.76%  github.com/dgraph-io/dgraph/protos/pb.(*Posting).Unmarshal

The portal did not allow me to upload the pb file. Let me know if you need anymore info.

(Daniel Mai) #5

@hbarthwal can you share the pb file? A link from Google Drive should work.

(Manish R Jain) #6

I also modified the settings in discuss, so now you should be able to upload files. This is very interesting profile, because it looks like mapToNquads is taking a lot of memory, which seems very strange to me. So, the heap profile can help us dig deeper.

(Himanshu Barthwal) #7

Uploading the pb file. pprof.dgraph.alloc_objects.alloc_space.inuse_objects.inuse_space.004.pb (57.1 KB)

(Daniel Mai) #8

Thanks for sharing the pprof data. It shows that our JSON parser is struggling to read in the huge JSON maps that’s in your dataset. If you can share your data privately (even a sample), we can look into improvements to our JSON parser.

You could also reduce the size of the JSON maps in the dataset. But given that your data is practically valid JSON, Dgraph can be doing a better job handling large JSON maps.

(Himanshu Barthwal) #9

@dmai You are right. I have files with millions of records in single json map. In fact each file is just one
json map which of course, can be avoided. I will make it so when I do the next bulk load. I think it would
make sense to include this in the documentation so that future users don’t run into the same issue. Do
you agree? Last but not the least, thanks for the awesome responses so far !