示例#1
0
    print
    for bsize in 1, 2, 4, 5, 8, 16, 32, 64:
        if os.path.exists(TMP_PATH):
            shutil.rmtree(TMP_PATH)
        st = acid.open('lmdb:%s' % (TMP_PATH, ))
        with st.begin(write=True):
            co = st.add_collection(
                'people',
                encoder=acid.encoders.make_json_encoder(sort_keys=True),
                compressor=packer)

            keys = [co.put(rec) for rec in recs]
            random.shuffle(keys)
            nextkey = iter(itertools.cycle(keys)).next

            before = store_size(st)
            itemcount = store_len(st)

            if bsize == 1:
                iterrecs, te = dotestiter()
                out('plain', before / 1024., itemcount, 1, 1, dotestget(), te,
                    iterrecs)
            co.strategy.batch(max_recs=bsize)

            itemcount = store_len(st)
            after = store_len(st)

            iterrecs, te = dotestiter()
            out(packer.name, after / 1024., itemcount,
                float(before) / after, bsize, dotestget(), te, iterrecs)
示例#2
0
for strat_klass in acid.core.BatchV2Strategy, acid.core.BatchStrategy, :
    compressor = acid.encoders.ZLIB

    store = acid.open('list:/')
    store.begin(write=True).__enter__()
    doink = store.add_collection('doink')
    prefix = acid.keylib.pack_int(doink.info['idx'], store.prefix)
    strat = strat_klass(prefix, store, compressor)
    doink.strategy = strat

    for word in words:
        doink.put(word)

    print 'done', strat, compressor
    print 'before len:', store_len(store)
    print 'before size:', store_size(store)
    print 'avgsz:', store_size(store) / store_len(store)
    print 'look/sec', rands(doink, rand)
    print

    strat.batch(max_bytes=2000)

    print 'done', strat, compressor
    print 'after len:', store_len(store)
    print 'after size:', store_size(store)
    print 'avgsz:', store_size(store) / store_len(store)
    print 'look/sec', rands(doink, rand)
    print

    li = store.engine.items[-1]
示例#3
0
文件: smallbatch.py 项目: dw/acid
for strat_klass in acid.core.BatchV2Strategy, acid.core.BatchStrategy, :
    compressor = acid.encoders.ZLIB

    store = acid.open('list:/')
    store.begin(write=True).__enter__()
    doink = store.add_collection('doink')
    prefix = acid.keylib.pack_int(doink.info['idx'], store.prefix)
    strat = strat_klass(prefix, store, compressor)
    doink.strategy = strat

    for word in words:
        doink.put(word)

    print 'done', strat, compressor
    print 'before len:', store_len(store)
    print 'before size:', store_size(store)
    print 'avgsz:', store_size(store)/store_len(store)
    print 'look/sec', rands(doink, rand)
    print

    strat.batch(max_bytes=2000)

    print 'done', strat, compressor
    print 'after len:', store_len(store)
    print 'after size:', store_size(store)
    print 'avgsz:', store_size(store)/store_len(store)
    print 'look/sec', rands(doink, rand)
    print

    li = store.engine.items[-1]
示例#4
0
文件: batch.py 项目: pombredanne/acid
for packer in acid.encoders.ZLIB, SNAPPY, LZ4:
    if not packer:
        continue

    print
    for bsize in 1, 2, 4, 5, 8, 16, 32, 64:
        if os.path.exists(TMP_PATH):
            shutil.rmtree(TMP_PATH)
        st = acid.open("lmdb:%s" % (TMP_PATH,))
        with st.begin(write=True):
            co = st.add_collection("people", encoder=acid.encoders.make_json_encoder(sort_keys=True), compressor=packer)

            keys = [co.put(rec) for rec in recs]
            random.shuffle(keys)
            nextkey = iter(itertools.cycle(keys)).next

            before = store_size(st)
            itemcount = store_len(st)

            if bsize == 1:
                iterrecs, te = dotestiter()
                out("plain", before / 1024.0, itemcount, 1, 1, dotestget(), te, iterrecs)
            co.strategy.batch(max_recs=bsize)

            itemcount = store_len(st)
            after = store_len(st)

            iterrecs, te = dotestiter()
            out(packer.name, after / 1024.0, itemcount, float(before) / after, bsize, dotestget(), te, iterrecs)