2019-10-16 13:41:50 +00:00
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package storage
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import (
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2021-09-22 15:58:48 +00:00
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"bytes"
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2021-10-05 12:13:19 +00:00
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"fmt"
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2021-09-22 15:58:48 +00:00
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"sort"
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2019-10-16 13:41:50 +00:00
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"testing"
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2021-10-05 12:13:19 +00:00
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"github.com/nspcc-dev/neo-go/internal/random"
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2021-09-22 15:58:48 +00:00
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"github.com/nspcc-dev/neo-go/pkg/util/slice"
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2019-10-16 13:41:50 +00:00
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"github.com/stretchr/testify/assert"
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"github.com/stretchr/testify/require"
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)
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2022-02-16 13:48:47 +00:00
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func TestMemCachedPutGetDelete(t *testing.T) {
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ps := NewMemoryStore()
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s := NewMemCachedStore(ps)
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key := []byte("foo")
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value := []byte("bar")
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s.Put(key, value)
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result, err := s.Get(key)
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assert.Nil(t, err)
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require.Equal(t, value, result)
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s.Delete(key)
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_, err = s.Get(key)
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assert.NotNil(t, err)
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assert.Equal(t, err, ErrKeyNotFound)
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// Double delete.
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s.Delete(key)
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_, err = s.Get(key)
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assert.NotNil(t, err)
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assert.Equal(t, err, ErrKeyNotFound)
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// Nonexistent.
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key = []byte("sparse")
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s.Delete(key)
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_, err = s.Get(key)
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assert.NotNil(t, err)
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assert.Equal(t, err, ErrKeyNotFound)
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}
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2020-03-27 12:40:23 +00:00
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func testMemCachedStorePersist(t *testing.T, ps Store) {
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2019-10-16 13:41:50 +00:00
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// cached Store
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ts := NewMemCachedStore(ps)
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// persisting nothing should do nothing
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c, err := ts.Persist()
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assert.Equal(t, nil, err)
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assert.Equal(t, 0, c)
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// persisting one key should result in one key in ps and nothing in ts
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ts.Put([]byte("key"), []byte("value"))
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checkBatch(t, ts, []KeyValueExists{{KeyValue: KeyValue{Key: []byte("key"), Value: []byte("value")}}}, nil)
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c, err = ts.Persist()
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checkBatch(t, ts, nil, nil)
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assert.Equal(t, nil, err)
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assert.Equal(t, 1, c)
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v, err := ps.Get([]byte("key"))
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assert.Equal(t, nil, err)
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assert.Equal(t, []byte("value"), v)
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v, err = ts.MemoryStore.Get([]byte("key"))
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assert.Equal(t, ErrKeyNotFound, err)
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assert.Equal(t, []byte(nil), v)
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// now we overwrite the previous `key` contents and also add `key2`,
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ts.Put([]byte("key"), []byte("newvalue"))
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ts.Put([]byte("key2"), []byte("value2"))
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// this is to check that now key is written into the ps before we do
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// persist
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v, err = ps.Get([]byte("key2"))
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assert.Equal(t, ErrKeyNotFound, err)
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assert.Equal(t, []byte(nil), v)
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checkBatch(t, ts, []KeyValueExists{
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{KeyValue: KeyValue{Key: []byte("key"), Value: []byte("newvalue")}, Exists: true},
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{KeyValue: KeyValue{Key: []byte("key2"), Value: []byte("value2")}},
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}, nil)
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// two keys should be persisted (one overwritten and one new) and
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// available in the ps
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c, err = ts.Persist()
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checkBatch(t, ts, nil, nil)
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assert.Equal(t, nil, err)
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assert.Equal(t, 2, c)
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v, err = ts.MemoryStore.Get([]byte("key"))
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assert.Equal(t, ErrKeyNotFound, err)
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assert.Equal(t, []byte(nil), v)
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v, err = ts.MemoryStore.Get([]byte("key2"))
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assert.Equal(t, ErrKeyNotFound, err)
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assert.Equal(t, []byte(nil), v)
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v, err = ps.Get([]byte("key"))
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assert.Equal(t, nil, err)
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assert.Equal(t, []byte("newvalue"), v)
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v, err = ps.Get([]byte("key2"))
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assert.Equal(t, nil, err)
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assert.Equal(t, []byte("value2"), v)
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checkBatch(t, ts, nil, nil)
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// we've persisted some values, make sure successive persist is a no-op
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c, err = ts.Persist()
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assert.Equal(t, nil, err)
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assert.Equal(t, 0, c)
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// test persisting deletions
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ts.Delete([]byte("key"))
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checkBatch(t, ts, nil, []KeyValueExists{{KeyValue: KeyValue{Key: []byte("key")}, Exists: true}})
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c, err = ts.Persist()
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checkBatch(t, ts, nil, nil)
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assert.Equal(t, nil, err)
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assert.Equal(t, 1, c)
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v, err = ps.Get([]byte("key"))
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assert.Equal(t, ErrKeyNotFound, err)
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assert.Equal(t, []byte(nil), v)
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v, err = ps.Get([]byte("key2"))
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assert.Equal(t, nil, err)
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assert.Equal(t, []byte("value2"), v)
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}
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func checkBatch(t *testing.T, ts *MemCachedStore, put []KeyValueExists, del []KeyValueExists) {
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b := ts.GetBatch()
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assert.Equal(t, len(put), len(b.Put), "wrong number of put elements in a batch")
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assert.Equal(t, len(del), len(b.Deleted), "wrong number of deleted elements in a batch")
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for i := range put {
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assert.Contains(t, b.Put, put[i])
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}
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for i := range del {
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assert.Contains(t, b.Deleted, del[i])
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}
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}
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2020-03-27 12:40:23 +00:00
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func TestMemCachedPersist(t *testing.T) {
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t.Run("MemoryStore", func(t *testing.T) {
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ps := NewMemoryStore()
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testMemCachedStorePersist(t, ps)
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})
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t.Run("MemoryCachedStore", func(t *testing.T) {
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ps1 := NewMemoryStore()
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ps2 := NewMemCachedStore(ps1)
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testMemCachedStorePersist(t, ps2)
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})
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t.Run("BoltDBStore", func(t *testing.T) {
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ps := newBoltStoreForTesting(t)
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t.Cleanup(func() {
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err := ps.Close()
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require.NoError(t, err)
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})
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2020-03-27 12:40:23 +00:00
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testMemCachedStorePersist(t, ps)
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})
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}
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2019-10-16 13:41:50 +00:00
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func TestCachedGetFromPersistent(t *testing.T) {
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key := []byte("key")
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value := []byte("value")
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ps := NewMemoryStore()
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ts := NewMemCachedStore(ps)
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assert.NoError(t, ps.PutChangeSet(map[string][]byte{string(key): value}, nil))
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val, err := ts.Get(key)
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assert.Nil(t, err)
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assert.Equal(t, value, val)
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ts.Delete(key)
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val, err = ts.Get(key)
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assert.Equal(t, err, ErrKeyNotFound)
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assert.Nil(t, val)
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}
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func TestCachedSeek(t *testing.T) {
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var (
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// Given this prefix...
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goodPrefix = []byte{'f'}
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// these pairs should be found...
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lowerKVs = []KeyValue{
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{[]byte("foo"), []byte("bar")},
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{[]byte("faa"), []byte("bra")},
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}
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// and these should be not.
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deletedKVs = []KeyValue{
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{[]byte("fee"), []byte("pow")},
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{[]byte("fii"), []byte("qaz")},
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}
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// and these should be not.
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updatedKVs = []KeyValue{
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{[]byte("fuu"), []byte("wop")},
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{[]byte("fyy"), []byte("zaq")},
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}
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ps = NewMemoryStore()
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ts = NewMemCachedStore(ps)
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)
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for _, v := range lowerKVs {
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require.NoError(t, ps.PutChangeSet(map[string][]byte{string(v.Key): v.Value}, nil))
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}
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for _, v := range deletedKVs {
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require.NoError(t, ps.PutChangeSet(map[string][]byte{string(v.Key): v.Value}, nil))
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ts.Delete(v.Key)
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}
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for _, v := range updatedKVs {
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require.NoError(t, ps.PutChangeSet(map[string][]byte{string(v.Key): v.Value}, nil))
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ts.Put(v.Key, v.Value)
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}
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foundKVs := make(map[string][]byte)
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ts.Seek(SeekRange{Prefix: goodPrefix}, func(k, v []byte) bool {
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foundKVs[string(k)] = v
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return true
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})
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assert.Equal(t, len(foundKVs), len(lowerKVs)+len(updatedKVs))
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for _, kv := range lowerKVs {
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assert.Equal(t, kv.Value, foundKVs[string(kv.Key)])
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}
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for _, kv := range deletedKVs {
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_, ok := foundKVs[string(kv.Key)]
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assert.Equal(t, false, ok)
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}
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for _, kv := range updatedKVs {
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assert.Equal(t, kv.Value, foundKVs[string(kv.Key)])
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}
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}
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2021-10-05 12:13:19 +00:00
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func benchmarkCachedSeek(t *testing.B, ps Store, psElementsCount, tsElementsCount int) {
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var (
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searchPrefix = []byte{1}
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badPrefix = []byte{2}
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lowerPrefixGood = append(searchPrefix, 1)
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lowerPrefixBad = append(badPrefix, 1)
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deletedPrefixGood = append(searchPrefix, 2)
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deletedPrefixBad = append(badPrefix, 2)
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updatedPrefixGood = append(searchPrefix, 3)
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updatedPrefixBad = append(badPrefix, 3)
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ts = NewMemCachedStore(ps)
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)
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for i := 0; i < psElementsCount; i++ {
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// lower KVs with matching prefix that should be found
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ts.Put(append(lowerPrefixGood, random.Bytes(10)...), []byte("value"))
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// lower KVs with non-matching prefix that shouldn't be found
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ts.Put(append(lowerPrefixBad, random.Bytes(10)...), []byte("value"))
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// deleted KVs with matching prefix that shouldn't be found
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key := append(deletedPrefixGood, random.Bytes(10)...)
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ts.Put(key, []byte("deleted"))
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if i < tsElementsCount {
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ts.Delete(key)
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}
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// deleted KVs with non-matching prefix that shouldn't be found
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key = append(deletedPrefixBad, random.Bytes(10)...)
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ts.Put(key, []byte("deleted"))
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if i < tsElementsCount {
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ts.Delete(key)
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}
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// updated KVs with matching prefix that should be found
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key = append(updatedPrefixGood, random.Bytes(10)...)
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ts.Put(key, []byte("stub"))
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if i < tsElementsCount {
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ts.Put(key, []byte("updated"))
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}
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// updated KVs with non-matching prefix that shouldn't be found
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key = append(updatedPrefixBad, random.Bytes(10)...)
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ts.Put(key, []byte("stub"))
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if i < tsElementsCount {
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ts.Put(key, []byte("updated"))
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}
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}
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_, err := ts.PersistSync()
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require.NoError(t, err)
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2021-10-05 12:13:19 +00:00
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t.ReportAllocs()
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t.ResetTimer()
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for n := 0; n < t.N; n++ {
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2022-01-17 17:41:51 +00:00
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ts.Seek(SeekRange{Prefix: searchPrefix}, func(k, v []byte) bool { return true })
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}
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t.StopTimer()
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}
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func BenchmarkCachedSeek(t *testing.B) {
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var stores = map[string]func(testing.TB) Store{
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"MemPS": func(t testing.TB) Store {
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return NewMemoryStore()
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},
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"BoltPS": newBoltStoreForTesting,
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"LevelPS": newLevelDBForTesting,
|
|
|
|
}
|
|
|
|
for psName, newPS := range stores {
|
|
|
|
for psCount := 100; psCount <= 10000; psCount *= 10 {
|
|
|
|
for tsCount := 10; tsCount <= psCount; tsCount *= 10 {
|
|
|
|
t.Run(fmt.Sprintf("%s_%dTSItems_%dPSItems", psName, tsCount, psCount), func(t *testing.B) {
|
|
|
|
ps := newPS(t)
|
|
|
|
benchmarkCachedSeek(t, ps, psCount, tsCount)
|
|
|
|
ps.Close()
|
|
|
|
})
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
func newMemCachedStoreForTesting(t testing.TB) Store {
|
2019-10-16 13:41:50 +00:00
|
|
|
return NewMemCachedStore(NewMemoryStore())
|
|
|
|
}
|
storage: allow accessing MemCachedStore during Persist
Persist by its definition doesn't change MemCachedStore visible state, all KV
pairs that were acessible via it before Persist remain accessible after
Persist. The only thing it does is flushing of the current set of KV pairs
from memory to peristent store. To do that it needs read-only access to the
current KV pair set, but technically it then replaces maps, so we have to use
full write lock which makes MemCachedStore inaccessible for the duration of
Persist. And Persist can take a lot of time, it's about disk access for
regular DBs.
What we do here is we create new in-memory maps for MemCachedStore before
flushing old ones to the persistent store. Then a fake persistent store is
created which actually is a MemCachedStore with old maps, so it has exactly
the same visible state. This Store is never accessed for writes, so we can
read it without taking any internal locks and at the same time we no longer
need write locks for original MemCachedStore, we're not using it. All of this
makes it possible to use MemCachedStore as normally reads are handled going
down to whatever level is needed and writes are handled by new maps. So while
Persist for (*Blockchain).dao does its most time-consuming work we can process
other blocks (reading data for transactions and persisting storeBlock caches
to (*Blockchain).dao).
The change was tested for performance with neo-bench (single node, 10 workers,
LevelDB) on two machines and block dump processing (RC4 testnet up to 62800
with VerifyBlocks set to false) on i7-8565U.
Reference results (bbe4e9cd7bb33428633586f080f64494cd6ac9cf):
Ryzen 9 5950X:
RPS 23616.969 22817.086 23222.378 ≈ 23218 ± 1.72%
TPS 23047.316 22608.578 22735.540 ≈ 22797 ± 0.99%
CPU % 23.434 25.553 23.848 ≈ 24.3 ± 4.63%
Mem MB 600.636 503.060 582.043 ≈ 562 ± 9.22%
Core i7-8565U:
RPS 6594.007 6499.501 6572.902 ≈ 6555 ± 0.76%
TPS 6561.680 6444.545 6510.120 ≈ 6505 ± 0.90%
CPU % 58.452 60.568 62.474 ≈ 60.5 ± 3.33%
Mem MB 234.893 285.067 269.081 ≈ 263 ± 9.75%
DB restore:
real 0m22.237s 0m23.471s 0m23.409s ≈ 23.04 ± 3.02%
user 0m35.435s 0m38.943s 0m39.247s ≈ 37.88 ± 5.59%
sys 0m3.085s 0m3.360s 0m3.144s ≈ 3.20 ± 4.53%
After the change:
Ryzen 9 5950X:
RPS 27747.349 27407.726 27520.210 ≈ 27558 ± 0.63% ↑ 18.69%
TPS 26992.010 26993.468 27010.966 ≈ 26999 ± 0.04% ↑ 18.43%
CPU % 28.928 28.096 29.105 ≈ 28.7 ± 1.88% ↑ 18.1%
Mem MB 760.385 726.320 756.118 ≈ 748 ± 2.48% ↑ 33.10%
Core i7-8565U:
RPS 7783.229 7628.409 7542.340 ≈ 7651 ± 1.60% ↑ 16.72%
TPS 7708.436 7607.397 7489.459 ≈ 7602 ± 1.44% ↑ 16.85%
CPU % 74.899 71.020 72.697 ≈ 72.9 ± 2.67% ↑ 20.50%
Mem MB 438.047 436.967 416.350 ≈ 430 ± 2.84% ↑ 63.50%
DB restore:
real 0m20.838s 0m21.895s 0m21.794s ≈ 21.51 ± 2.71% ↓ 6.64%
user 0m39.091s 0m40.565s 0m41.493s ≈ 40.38 ± 3.00% ↑ 6.60%
sys 0m3.184s 0m2.923s 0m3.062s ≈ 3.06 ± 4.27% ↓ 4.38%
It obviously uses more memory now and utilizes CPU more aggressively, but at
the same time it allows to improve all relevant metrics and finally reach a
situation where we process 50K transactions in less than second on Ryzen 9
5950X (going higher than 25K TPS). The other observation is much more stable
block time, on Ryzen 9 it's as close to 1 second as it could be.
2021-07-30 20:35:03 +00:00
|
|
|
|
|
|
|
type BadStore struct {
|
|
|
|
onPutBatch func()
|
|
|
|
}
|
|
|
|
|
|
|
|
func (b *BadStore) Delete(k []byte) error {
|
|
|
|
return nil
|
|
|
|
}
|
|
|
|
func (b *BadStore) Get([]byte) ([]byte, error) {
|
|
|
|
return nil, ErrKeyNotFound
|
|
|
|
}
|
|
|
|
func (b *BadStore) Put(k, v []byte) error {
|
|
|
|
return nil
|
|
|
|
}
|
storage: use two maps for MemoryStore
Simple and dumb as it is, this allows to separate contract storage from other
things and dramatically improve Seek() time over storage (even though it's
still unordered!) which in turn improves block processing speed.
LevelDB LevelDB (KeepOnlyLatest) BoltDB BoltDB (KeepOnlyLatest)
Master real 16m27,936s real 10m9,440s real 16m39,369s real 8m1,227s
user 20m12,619s user 26m13,925s user 18m9,162s user 18m5,846s
sys 2m56,377s sys 1m32,051s sys 9m52,576s sys 2m9,455s
2 maps real 10m49,495s real 8m53,342s real 11m46,204s real 5m56,043s
user 14m19,922s user 24m6,225s user 13m25,691s user 15m4,694s
sys 1m53,021s sys 1m23,006s sys 4m31,735s sys 2m8,714s
neo-bench performance is mostly unaffected, ~0.5% for 1-1 test and 4% for
10K-10K test both fall within regular test error range.
2022-02-15 16:07:59 +00:00
|
|
|
func (b *BadStore) PutChangeSet(_ map[string][]byte, _ map[string][]byte) error {
|
storage: allow accessing MemCachedStore during Persist
Persist by its definition doesn't change MemCachedStore visible state, all KV
pairs that were acessible via it before Persist remain accessible after
Persist. The only thing it does is flushing of the current set of KV pairs
from memory to peristent store. To do that it needs read-only access to the
current KV pair set, but technically it then replaces maps, so we have to use
full write lock which makes MemCachedStore inaccessible for the duration of
Persist. And Persist can take a lot of time, it's about disk access for
regular DBs.
What we do here is we create new in-memory maps for MemCachedStore before
flushing old ones to the persistent store. Then a fake persistent store is
created which actually is a MemCachedStore with old maps, so it has exactly
the same visible state. This Store is never accessed for writes, so we can
read it without taking any internal locks and at the same time we no longer
need write locks for original MemCachedStore, we're not using it. All of this
makes it possible to use MemCachedStore as normally reads are handled going
down to whatever level is needed and writes are handled by new maps. So while
Persist for (*Blockchain).dao does its most time-consuming work we can process
other blocks (reading data for transactions and persisting storeBlock caches
to (*Blockchain).dao).
The change was tested for performance with neo-bench (single node, 10 workers,
LevelDB) on two machines and block dump processing (RC4 testnet up to 62800
with VerifyBlocks set to false) on i7-8565U.
Reference results (bbe4e9cd7bb33428633586f080f64494cd6ac9cf):
Ryzen 9 5950X:
RPS 23616.969 22817.086 23222.378 ≈ 23218 ± 1.72%
TPS 23047.316 22608.578 22735.540 ≈ 22797 ± 0.99%
CPU % 23.434 25.553 23.848 ≈ 24.3 ± 4.63%
Mem MB 600.636 503.060 582.043 ≈ 562 ± 9.22%
Core i7-8565U:
RPS 6594.007 6499.501 6572.902 ≈ 6555 ± 0.76%
TPS 6561.680 6444.545 6510.120 ≈ 6505 ± 0.90%
CPU % 58.452 60.568 62.474 ≈ 60.5 ± 3.33%
Mem MB 234.893 285.067 269.081 ≈ 263 ± 9.75%
DB restore:
real 0m22.237s 0m23.471s 0m23.409s ≈ 23.04 ± 3.02%
user 0m35.435s 0m38.943s 0m39.247s ≈ 37.88 ± 5.59%
sys 0m3.085s 0m3.360s 0m3.144s ≈ 3.20 ± 4.53%
After the change:
Ryzen 9 5950X:
RPS 27747.349 27407.726 27520.210 ≈ 27558 ± 0.63% ↑ 18.69%
TPS 26992.010 26993.468 27010.966 ≈ 26999 ± 0.04% ↑ 18.43%
CPU % 28.928 28.096 29.105 ≈ 28.7 ± 1.88% ↑ 18.1%
Mem MB 760.385 726.320 756.118 ≈ 748 ± 2.48% ↑ 33.10%
Core i7-8565U:
RPS 7783.229 7628.409 7542.340 ≈ 7651 ± 1.60% ↑ 16.72%
TPS 7708.436 7607.397 7489.459 ≈ 7602 ± 1.44% ↑ 16.85%
CPU % 74.899 71.020 72.697 ≈ 72.9 ± 2.67% ↑ 20.50%
Mem MB 438.047 436.967 416.350 ≈ 430 ± 2.84% ↑ 63.50%
DB restore:
real 0m20.838s 0m21.895s 0m21.794s ≈ 21.51 ± 2.71% ↓ 6.64%
user 0m39.091s 0m40.565s 0m41.493s ≈ 40.38 ± 3.00% ↑ 6.60%
sys 0m3.184s 0m2.923s 0m3.062s ≈ 3.06 ± 4.27% ↓ 4.38%
It obviously uses more memory now and utilizes CPU more aggressively, but at
the same time it allows to improve all relevant metrics and finally reach a
situation where we process 50K transactions in less than second on Ryzen 9
5950X (going higher than 25K TPS). The other observation is much more stable
block time, on Ryzen 9 it's as close to 1 second as it could be.
2021-07-30 20:35:03 +00:00
|
|
|
b.onPutBatch()
|
|
|
|
return ErrKeyNotFound
|
|
|
|
}
|
2022-01-17 17:41:51 +00:00
|
|
|
func (b *BadStore) Seek(rng SeekRange, f func(k, v []byte) bool) {
|
storage: allow accessing MemCachedStore during Persist
Persist by its definition doesn't change MemCachedStore visible state, all KV
pairs that were acessible via it before Persist remain accessible after
Persist. The only thing it does is flushing of the current set of KV pairs
from memory to peristent store. To do that it needs read-only access to the
current KV pair set, but technically it then replaces maps, so we have to use
full write lock which makes MemCachedStore inaccessible for the duration of
Persist. And Persist can take a lot of time, it's about disk access for
regular DBs.
What we do here is we create new in-memory maps for MemCachedStore before
flushing old ones to the persistent store. Then a fake persistent store is
created which actually is a MemCachedStore with old maps, so it has exactly
the same visible state. This Store is never accessed for writes, so we can
read it without taking any internal locks and at the same time we no longer
need write locks for original MemCachedStore, we're not using it. All of this
makes it possible to use MemCachedStore as normally reads are handled going
down to whatever level is needed and writes are handled by new maps. So while
Persist for (*Blockchain).dao does its most time-consuming work we can process
other blocks (reading data for transactions and persisting storeBlock caches
to (*Blockchain).dao).
The change was tested for performance with neo-bench (single node, 10 workers,
LevelDB) on two machines and block dump processing (RC4 testnet up to 62800
with VerifyBlocks set to false) on i7-8565U.
Reference results (bbe4e9cd7bb33428633586f080f64494cd6ac9cf):
Ryzen 9 5950X:
RPS 23616.969 22817.086 23222.378 ≈ 23218 ± 1.72%
TPS 23047.316 22608.578 22735.540 ≈ 22797 ± 0.99%
CPU % 23.434 25.553 23.848 ≈ 24.3 ± 4.63%
Mem MB 600.636 503.060 582.043 ≈ 562 ± 9.22%
Core i7-8565U:
RPS 6594.007 6499.501 6572.902 ≈ 6555 ± 0.76%
TPS 6561.680 6444.545 6510.120 ≈ 6505 ± 0.90%
CPU % 58.452 60.568 62.474 ≈ 60.5 ± 3.33%
Mem MB 234.893 285.067 269.081 ≈ 263 ± 9.75%
DB restore:
real 0m22.237s 0m23.471s 0m23.409s ≈ 23.04 ± 3.02%
user 0m35.435s 0m38.943s 0m39.247s ≈ 37.88 ± 5.59%
sys 0m3.085s 0m3.360s 0m3.144s ≈ 3.20 ± 4.53%
After the change:
Ryzen 9 5950X:
RPS 27747.349 27407.726 27520.210 ≈ 27558 ± 0.63% ↑ 18.69%
TPS 26992.010 26993.468 27010.966 ≈ 26999 ± 0.04% ↑ 18.43%
CPU % 28.928 28.096 29.105 ≈ 28.7 ± 1.88% ↑ 18.1%
Mem MB 760.385 726.320 756.118 ≈ 748 ± 2.48% ↑ 33.10%
Core i7-8565U:
RPS 7783.229 7628.409 7542.340 ≈ 7651 ± 1.60% ↑ 16.72%
TPS 7708.436 7607.397 7489.459 ≈ 7602 ± 1.44% ↑ 16.85%
CPU % 74.899 71.020 72.697 ≈ 72.9 ± 2.67% ↑ 20.50%
Mem MB 438.047 436.967 416.350 ≈ 430 ± 2.84% ↑ 63.50%
DB restore:
real 0m20.838s 0m21.895s 0m21.794s ≈ 21.51 ± 2.71% ↓ 6.64%
user 0m39.091s 0m40.565s 0m41.493s ≈ 40.38 ± 3.00% ↑ 6.60%
sys 0m3.184s 0m2.923s 0m3.062s ≈ 3.06 ± 4.27% ↓ 4.38%
It obviously uses more memory now and utilizes CPU more aggressively, but at
the same time it allows to improve all relevant metrics and finally reach a
situation where we process 50K transactions in less than second on Ryzen 9
5950X (going higher than 25K TPS). The other observation is much more stable
block time, on Ryzen 9 it's as close to 1 second as it could be.
2021-07-30 20:35:03 +00:00
|
|
|
}
|
2022-02-11 17:35:45 +00:00
|
|
|
func (b *BadStore) SeekGC(rng SeekRange, keep func(k, v []byte) bool) error {
|
|
|
|
return nil
|
|
|
|
}
|
storage: allow accessing MemCachedStore during Persist
Persist by its definition doesn't change MemCachedStore visible state, all KV
pairs that were acessible via it before Persist remain accessible after
Persist. The only thing it does is flushing of the current set of KV pairs
from memory to peristent store. To do that it needs read-only access to the
current KV pair set, but technically it then replaces maps, so we have to use
full write lock which makes MemCachedStore inaccessible for the duration of
Persist. And Persist can take a lot of time, it's about disk access for
regular DBs.
What we do here is we create new in-memory maps for MemCachedStore before
flushing old ones to the persistent store. Then a fake persistent store is
created which actually is a MemCachedStore with old maps, so it has exactly
the same visible state. This Store is never accessed for writes, so we can
read it without taking any internal locks and at the same time we no longer
need write locks for original MemCachedStore, we're not using it. All of this
makes it possible to use MemCachedStore as normally reads are handled going
down to whatever level is needed and writes are handled by new maps. So while
Persist for (*Blockchain).dao does its most time-consuming work we can process
other blocks (reading data for transactions and persisting storeBlock caches
to (*Blockchain).dao).
The change was tested for performance with neo-bench (single node, 10 workers,
LevelDB) on two machines and block dump processing (RC4 testnet up to 62800
with VerifyBlocks set to false) on i7-8565U.
Reference results (bbe4e9cd7bb33428633586f080f64494cd6ac9cf):
Ryzen 9 5950X:
RPS 23616.969 22817.086 23222.378 ≈ 23218 ± 1.72%
TPS 23047.316 22608.578 22735.540 ≈ 22797 ± 0.99%
CPU % 23.434 25.553 23.848 ≈ 24.3 ± 4.63%
Mem MB 600.636 503.060 582.043 ≈ 562 ± 9.22%
Core i7-8565U:
RPS 6594.007 6499.501 6572.902 ≈ 6555 ± 0.76%
TPS 6561.680 6444.545 6510.120 ≈ 6505 ± 0.90%
CPU % 58.452 60.568 62.474 ≈ 60.5 ± 3.33%
Mem MB 234.893 285.067 269.081 ≈ 263 ± 9.75%
DB restore:
real 0m22.237s 0m23.471s 0m23.409s ≈ 23.04 ± 3.02%
user 0m35.435s 0m38.943s 0m39.247s ≈ 37.88 ± 5.59%
sys 0m3.085s 0m3.360s 0m3.144s ≈ 3.20 ± 4.53%
After the change:
Ryzen 9 5950X:
RPS 27747.349 27407.726 27520.210 ≈ 27558 ± 0.63% ↑ 18.69%
TPS 26992.010 26993.468 27010.966 ≈ 26999 ± 0.04% ↑ 18.43%
CPU % 28.928 28.096 29.105 ≈ 28.7 ± 1.88% ↑ 18.1%
Mem MB 760.385 726.320 756.118 ≈ 748 ± 2.48% ↑ 33.10%
Core i7-8565U:
RPS 7783.229 7628.409 7542.340 ≈ 7651 ± 1.60% ↑ 16.72%
TPS 7708.436 7607.397 7489.459 ≈ 7602 ± 1.44% ↑ 16.85%
CPU % 74.899 71.020 72.697 ≈ 72.9 ± 2.67% ↑ 20.50%
Mem MB 438.047 436.967 416.350 ≈ 430 ± 2.84% ↑ 63.50%
DB restore:
real 0m20.838s 0m21.895s 0m21.794s ≈ 21.51 ± 2.71% ↓ 6.64%
user 0m39.091s 0m40.565s 0m41.493s ≈ 40.38 ± 3.00% ↑ 6.60%
sys 0m3.184s 0m2.923s 0m3.062s ≈ 3.06 ± 4.27% ↓ 4.38%
It obviously uses more memory now and utilizes CPU more aggressively, but at
the same time it allows to improve all relevant metrics and finally reach a
situation where we process 50K transactions in less than second on Ryzen 9
5950X (going higher than 25K TPS). The other observation is much more stable
block time, on Ryzen 9 it's as close to 1 second as it could be.
2021-07-30 20:35:03 +00:00
|
|
|
func (b *BadStore) Close() error {
|
|
|
|
return nil
|
|
|
|
}
|
|
|
|
|
|
|
|
func TestMemCachedPersistFailing(t *testing.T) {
|
|
|
|
var (
|
|
|
|
bs BadStore
|
|
|
|
t1 = []byte("t1")
|
|
|
|
t2 = []byte("t2")
|
|
|
|
b1 = []byte("b1")
|
|
|
|
)
|
|
|
|
// cached Store
|
|
|
|
ts := NewMemCachedStore(&bs)
|
|
|
|
// Set a pair of keys.
|
2022-02-16 14:48:15 +00:00
|
|
|
ts.Put(t1, t1)
|
|
|
|
ts.Put(t2, t2)
|
storage: allow accessing MemCachedStore during Persist
Persist by its definition doesn't change MemCachedStore visible state, all KV
pairs that were acessible via it before Persist remain accessible after
Persist. The only thing it does is flushing of the current set of KV pairs
from memory to peristent store. To do that it needs read-only access to the
current KV pair set, but technically it then replaces maps, so we have to use
full write lock which makes MemCachedStore inaccessible for the duration of
Persist. And Persist can take a lot of time, it's about disk access for
regular DBs.
What we do here is we create new in-memory maps for MemCachedStore before
flushing old ones to the persistent store. Then a fake persistent store is
created which actually is a MemCachedStore with old maps, so it has exactly
the same visible state. This Store is never accessed for writes, so we can
read it without taking any internal locks and at the same time we no longer
need write locks for original MemCachedStore, we're not using it. All of this
makes it possible to use MemCachedStore as normally reads are handled going
down to whatever level is needed and writes are handled by new maps. So while
Persist for (*Blockchain).dao does its most time-consuming work we can process
other blocks (reading data for transactions and persisting storeBlock caches
to (*Blockchain).dao).
The change was tested for performance with neo-bench (single node, 10 workers,
LevelDB) on two machines and block dump processing (RC4 testnet up to 62800
with VerifyBlocks set to false) on i7-8565U.
Reference results (bbe4e9cd7bb33428633586f080f64494cd6ac9cf):
Ryzen 9 5950X:
RPS 23616.969 22817.086 23222.378 ≈ 23218 ± 1.72%
TPS 23047.316 22608.578 22735.540 ≈ 22797 ± 0.99%
CPU % 23.434 25.553 23.848 ≈ 24.3 ± 4.63%
Mem MB 600.636 503.060 582.043 ≈ 562 ± 9.22%
Core i7-8565U:
RPS 6594.007 6499.501 6572.902 ≈ 6555 ± 0.76%
TPS 6561.680 6444.545 6510.120 ≈ 6505 ± 0.90%
CPU % 58.452 60.568 62.474 ≈ 60.5 ± 3.33%
Mem MB 234.893 285.067 269.081 ≈ 263 ± 9.75%
DB restore:
real 0m22.237s 0m23.471s 0m23.409s ≈ 23.04 ± 3.02%
user 0m35.435s 0m38.943s 0m39.247s ≈ 37.88 ± 5.59%
sys 0m3.085s 0m3.360s 0m3.144s ≈ 3.20 ± 4.53%
After the change:
Ryzen 9 5950X:
RPS 27747.349 27407.726 27520.210 ≈ 27558 ± 0.63% ↑ 18.69%
TPS 26992.010 26993.468 27010.966 ≈ 26999 ± 0.04% ↑ 18.43%
CPU % 28.928 28.096 29.105 ≈ 28.7 ± 1.88% ↑ 18.1%
Mem MB 760.385 726.320 756.118 ≈ 748 ± 2.48% ↑ 33.10%
Core i7-8565U:
RPS 7783.229 7628.409 7542.340 ≈ 7651 ± 1.60% ↑ 16.72%
TPS 7708.436 7607.397 7489.459 ≈ 7602 ± 1.44% ↑ 16.85%
CPU % 74.899 71.020 72.697 ≈ 72.9 ± 2.67% ↑ 20.50%
Mem MB 438.047 436.967 416.350 ≈ 430 ± 2.84% ↑ 63.50%
DB restore:
real 0m20.838s 0m21.895s 0m21.794s ≈ 21.51 ± 2.71% ↓ 6.64%
user 0m39.091s 0m40.565s 0m41.493s ≈ 40.38 ± 3.00% ↑ 6.60%
sys 0m3.184s 0m2.923s 0m3.062s ≈ 3.06 ± 4.27% ↓ 4.38%
It obviously uses more memory now and utilizes CPU more aggressively, but at
the same time it allows to improve all relevant metrics and finally reach a
situation where we process 50K transactions in less than second on Ryzen 9
5950X (going higher than 25K TPS). The other observation is much more stable
block time, on Ryzen 9 it's as close to 1 second as it could be.
2021-07-30 20:35:03 +00:00
|
|
|
// This will be called during Persist().
|
|
|
|
bs.onPutBatch = func() {
|
|
|
|
// Drop one, add one.
|
2022-02-16 14:48:15 +00:00
|
|
|
ts.Put(b1, b1)
|
|
|
|
ts.Delete(t1)
|
storage: allow accessing MemCachedStore during Persist
Persist by its definition doesn't change MemCachedStore visible state, all KV
pairs that were acessible via it before Persist remain accessible after
Persist. The only thing it does is flushing of the current set of KV pairs
from memory to peristent store. To do that it needs read-only access to the
current KV pair set, but technically it then replaces maps, so we have to use
full write lock which makes MemCachedStore inaccessible for the duration of
Persist. And Persist can take a lot of time, it's about disk access for
regular DBs.
What we do here is we create new in-memory maps for MemCachedStore before
flushing old ones to the persistent store. Then a fake persistent store is
created which actually is a MemCachedStore with old maps, so it has exactly
the same visible state. This Store is never accessed for writes, so we can
read it without taking any internal locks and at the same time we no longer
need write locks for original MemCachedStore, we're not using it. All of this
makes it possible to use MemCachedStore as normally reads are handled going
down to whatever level is needed and writes are handled by new maps. So while
Persist for (*Blockchain).dao does its most time-consuming work we can process
other blocks (reading data for transactions and persisting storeBlock caches
to (*Blockchain).dao).
The change was tested for performance with neo-bench (single node, 10 workers,
LevelDB) on two machines and block dump processing (RC4 testnet up to 62800
with VerifyBlocks set to false) on i7-8565U.
Reference results (bbe4e9cd7bb33428633586f080f64494cd6ac9cf):
Ryzen 9 5950X:
RPS 23616.969 22817.086 23222.378 ≈ 23218 ± 1.72%
TPS 23047.316 22608.578 22735.540 ≈ 22797 ± 0.99%
CPU % 23.434 25.553 23.848 ≈ 24.3 ± 4.63%
Mem MB 600.636 503.060 582.043 ≈ 562 ± 9.22%
Core i7-8565U:
RPS 6594.007 6499.501 6572.902 ≈ 6555 ± 0.76%
TPS 6561.680 6444.545 6510.120 ≈ 6505 ± 0.90%
CPU % 58.452 60.568 62.474 ≈ 60.5 ± 3.33%
Mem MB 234.893 285.067 269.081 ≈ 263 ± 9.75%
DB restore:
real 0m22.237s 0m23.471s 0m23.409s ≈ 23.04 ± 3.02%
user 0m35.435s 0m38.943s 0m39.247s ≈ 37.88 ± 5.59%
sys 0m3.085s 0m3.360s 0m3.144s ≈ 3.20 ± 4.53%
After the change:
Ryzen 9 5950X:
RPS 27747.349 27407.726 27520.210 ≈ 27558 ± 0.63% ↑ 18.69%
TPS 26992.010 26993.468 27010.966 ≈ 26999 ± 0.04% ↑ 18.43%
CPU % 28.928 28.096 29.105 ≈ 28.7 ± 1.88% ↑ 18.1%
Mem MB 760.385 726.320 756.118 ≈ 748 ± 2.48% ↑ 33.10%
Core i7-8565U:
RPS 7783.229 7628.409 7542.340 ≈ 7651 ± 1.60% ↑ 16.72%
TPS 7708.436 7607.397 7489.459 ≈ 7602 ± 1.44% ↑ 16.85%
CPU % 74.899 71.020 72.697 ≈ 72.9 ± 2.67% ↑ 20.50%
Mem MB 438.047 436.967 416.350 ≈ 430 ± 2.84% ↑ 63.50%
DB restore:
real 0m20.838s 0m21.895s 0m21.794s ≈ 21.51 ± 2.71% ↓ 6.64%
user 0m39.091s 0m40.565s 0m41.493s ≈ 40.38 ± 3.00% ↑ 6.60%
sys 0m3.184s 0m2.923s 0m3.062s ≈ 3.06 ± 4.27% ↓ 4.38%
It obviously uses more memory now and utilizes CPU more aggressively, but at
the same time it allows to improve all relevant metrics and finally reach a
situation where we process 50K transactions in less than second on Ryzen 9
5950X (going higher than 25K TPS). The other observation is much more stable
block time, on Ryzen 9 it's as close to 1 second as it could be.
2021-07-30 20:35:03 +00:00
|
|
|
}
|
|
|
|
_, err := ts.Persist()
|
|
|
|
require.Error(t, err)
|
|
|
|
// PutBatch() failed in Persist, but we still should have proper state.
|
|
|
|
_, err = ts.Get(t1)
|
|
|
|
require.Error(t, err)
|
|
|
|
res, err := ts.Get(t2)
|
|
|
|
require.NoError(t, err)
|
|
|
|
require.Equal(t, t2, res)
|
|
|
|
res, err = ts.Get(b1)
|
|
|
|
require.NoError(t, err)
|
|
|
|
require.Equal(t, b1, res)
|
|
|
|
}
|
2021-09-22 15:58:48 +00:00
|
|
|
|
2022-02-16 16:13:06 +00:00
|
|
|
func TestPrivateMemCachedPersistFailing(t *testing.T) {
|
|
|
|
var (
|
|
|
|
bs BadStore
|
|
|
|
t1 = []byte("t1")
|
|
|
|
t2 = []byte("t2")
|
|
|
|
)
|
|
|
|
// cached Store
|
|
|
|
ts := NewPrivateMemCachedStore(&bs)
|
|
|
|
// Set a pair of keys.
|
|
|
|
ts.Put(t1, t1)
|
|
|
|
ts.Put(t2, t2)
|
|
|
|
// This will be called during Persist().
|
|
|
|
bs.onPutBatch = func() {}
|
|
|
|
|
|
|
|
_, err := ts.Persist()
|
|
|
|
require.Error(t, err)
|
|
|
|
// PutBatch() failed in Persist, but we still should have proper state.
|
|
|
|
res, err := ts.Get(t1)
|
|
|
|
require.NoError(t, err)
|
|
|
|
require.Equal(t, t1, res)
|
|
|
|
res, err = ts.Get(t2)
|
|
|
|
require.NoError(t, err)
|
|
|
|
require.Equal(t, t2, res)
|
|
|
|
}
|
|
|
|
|
2021-09-22 15:58:48 +00:00
|
|
|
func TestCachedSeekSorting(t *testing.T) {
|
|
|
|
var (
|
|
|
|
// Given this prefix...
|
|
|
|
goodPrefix = []byte{1}
|
|
|
|
// these pairs should be found...
|
2021-12-28 14:07:52 +00:00
|
|
|
lowerKVs = []KeyValue{
|
|
|
|
{[]byte{1, 2, 3}, []byte("bra")},
|
|
|
|
{[]byte{1, 2, 5}, []byte("bar")},
|
|
|
|
{[]byte{1, 3, 3}, []byte("bra")},
|
|
|
|
{[]byte{1, 3, 5}, []byte("bra")},
|
2021-09-22 15:58:48 +00:00
|
|
|
}
|
|
|
|
// and these should be not.
|
2021-12-28 14:07:52 +00:00
|
|
|
deletedKVs = []KeyValue{
|
|
|
|
{[]byte{1, 7, 3}, []byte("pow")},
|
|
|
|
{[]byte{1, 7, 4}, []byte("qaz")},
|
2021-09-22 15:58:48 +00:00
|
|
|
}
|
|
|
|
// and these should be not.
|
2021-12-28 14:07:52 +00:00
|
|
|
updatedKVs = []KeyValue{
|
|
|
|
{[]byte{1, 2, 4}, []byte("zaq")},
|
|
|
|
{[]byte{1, 2, 6}, []byte("zaq")},
|
|
|
|
{[]byte{1, 3, 2}, []byte("wop")},
|
|
|
|
{[]byte{1, 3, 4}, []byte("zaq")},
|
2021-09-22 15:58:48 +00:00
|
|
|
}
|
|
|
|
)
|
2022-02-16 16:13:06 +00:00
|
|
|
for _, newCached := range []func(Store) *MemCachedStore{NewMemCachedStore, NewPrivateMemCachedStore} {
|
|
|
|
ps := NewMemoryStore()
|
|
|
|
ts := newCached(ps)
|
|
|
|
for _, v := range lowerKVs {
|
|
|
|
require.NoError(t, ps.PutChangeSet(map[string][]byte{string(v.Key): v.Value}, nil))
|
|
|
|
}
|
|
|
|
for _, v := range deletedKVs {
|
|
|
|
require.NoError(t, ps.PutChangeSet(map[string][]byte{string(v.Key): v.Value}, nil))
|
|
|
|
ts.Delete(v.Key)
|
|
|
|
}
|
|
|
|
for _, v := range updatedKVs {
|
|
|
|
require.NoError(t, ps.PutChangeSet(map[string][]byte{string(v.Key): v.Value}, nil))
|
|
|
|
ts.Put(v.Key, v.Value)
|
|
|
|
}
|
|
|
|
var foundKVs []KeyValue
|
|
|
|
ts.Seek(SeekRange{Prefix: goodPrefix}, func(k, v []byte) bool {
|
|
|
|
foundKVs = append(foundKVs, KeyValue{Key: slice.Copy(k), Value: slice.Copy(v)})
|
|
|
|
return true
|
|
|
|
})
|
|
|
|
assert.Equal(t, len(foundKVs), len(lowerKVs)+len(updatedKVs))
|
|
|
|
expected := append(lowerKVs, updatedKVs...)
|
|
|
|
sort.Slice(expected, func(i, j int) bool {
|
|
|
|
return bytes.Compare(expected[i].Key, expected[j].Key) < 0
|
|
|
|
})
|
|
|
|
require.Equal(t, expected, foundKVs)
|
2021-09-22 15:58:48 +00:00
|
|
|
}
|
|
|
|
}
|