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| 1 | +# Nebula Algorithm test |
| 2 | + |
| 3 | +## Data preparation |
| 4 | + |
| 5 | +1. Install Nebula Graph 3.0.0 |
| 6 | + * cluster info: |
| 7 | + |
| 8 | + `3 metad, 3 graphd, 3 storaged` |
| 9 | + |
| 10 | + * space info: |
| 11 | + |
| 12 | + |Name |Partition Number|Replica Factor|Charset|Vid Type| |
| 13 | + |-----------|----------------|--------------|-------|--------| |
| 14 | + |algo_space | 100 | 1 | uft8 | int64 | |
| 15 | + |
| 16 | +2. Put LDBC sf100 dataset to HDFS: /ldbc/sf100 |
| 17 | + |
| 18 | + We use Nebula Exchange to import ldbc sf100 dataset into Nebula, importing details see: https://github.com/vesoft-inc/nebula-exchange/tree/master/bench |
| 19 | + |
| 20 | + |
| 21 | +## Test algorithms with HDFS datasource and HDFS data sink |
| 22 | +We use LDBC's `forum_hasMember_person` edge dataset to test the algorithms. |
| 23 | + |
| 24 | + | algorithms | data amount | concurrency |executor-memory|iter| other params | duration| |
| 25 | + |------------------|----------------|-------------|---------------|----|----------------------|---------| |
| 26 | + | pagerank | 180 millions | 30 | 45G | 10 |resetProb:0.15 | 1.1min | |
| 27 | + | trianglecount | 180 millions | 30 | 45G | - | - | 19min | |
| 28 | + | lpa | 180 millions | 30 | 45G | 10 | - | 11min | |
| 29 | + | wcc | 180 millions | 30 | 45G | 10 | - | 40s | |
| 30 | + | scc | 180 millions | 30 | 45G | 10 | - | 38s | |
| 31 | + |clustercoefficient| 180 millions | 30 | 45G | - | - | 25min | |
| 32 | + | kcore | 180 millions | 30 | 45G | 10 | degree:1 | 1min | |
| 33 | + | degreeCentrality | 180 millions | 30 | 45G | - | - | 34s | |
| 34 | + | louvain | 180 millions | 30 | 45G | 10 |internalIter:5,tol:0.5| 10min | |
| 35 | + | BFS | 180 millions | 30 | 45G | 10 |root:17592186046139 | 52s | |
| 36 | + | HANP | 180 millions | 30 | 45G | 10 |hop:0.1,preference:1.0| 17min | |
| 37 | + | closeness | 180 millions | 30 | 45G | - | - | 17min | |
| 38 | + |
| 39 | +# Test algorithms with Nebula datasource and Nebula data sink |
| 40 | +We use Nebula's `HAS_MEMBER` edge type to test the algorithms, and the result is writen into new tag. |
| 41 | + |
| 42 | + | algorithms | data amount | concurrency |executor-memory|iter| other params | duration| |
| 43 | + |------------------|----------------|-------------|---------------|----|----------------------|---------| |
| 44 | + | pagerank | 180 millions | 30 | 45G | 10 |resetProb:0.15 | 5.2min | |
| 45 | + | trianglecount | 180 millions | 30 | 45G | - | - | 12min | |
| 46 | + | lpa | 180 millions | 30 | 45G | 10 | - | 44min | |
| 47 | + | wcc | 180 millions | 30 | 45G | 10 | - | 1.8min | |
| 48 | + | scc | 180 millions | 30 | 45G | 10 | - | 2min | |
| 49 | + |clustercoefficient| 180 millions | 30 | 45G | - | - | 11min | |
| 50 | + | kcore | 180 millions | 30 | 45G | 10 | degree:1 | 3.2min | |
| 51 | + | degreeCentrality | 180 millions | 30 | 45G | - | - | 3.6min | |
| 52 | + | louvain | 180 millions | 30 | 45G | 10 |internalIter:5,tol:0.5| 14min | |
| 53 | + | BFS | 180 millions | 30 | 45G | 10 |root:17592186046139 | 2.3min | |
| 54 | + | HANP | 180 millions | 30 | 45G | 10 |hop:0.1,preference:1.0| 52min | |
| 55 | + | closeness | 180 millions | 30 | 45G | - | - | 42min | |
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