在 h2o 中加载大于内存大小的数据

Question

我正在尝试在 h2o 中加载大于内存大小的数据。

H2o blog 提到：A note on Bigger Data and GC: We do a user-mode swap-to-disk when the Java heap gets too full, i.e., you’re using more Big Data than physical DRAM. We won’t die with a GC death-spiral, but we will degrade to out-of-core speeds. We’ll go as fast as the disk will allow. I’ve personally tested loading a 12Gb dataset into a 2Gb (32bit) JVM; it took about 5 minutes to load the data, and another 5 minutes to run a Logistic Regression.

这是连接到 h2o 3.6.0.8 的 R 代码：

h2o.init(max_mem_size = '60m') # alloting 60mb for h2o, R is running on 8GB RAM machine

给予

java version "1.8.0_65"
Java(TM) SE Runtime Environment (build 1.8.0_65-b17)
Java HotSpot(TM) 64-Bit Server VM (build 25.65-b01, mixed mode)

.Successfully connected to http://127.0.0.1:54321/ 

R is connected to the H2O cluster: 
    H2O cluster uptime:         2 seconds 561 milliseconds 
    H2O cluster version:        3.6.0.8 
    H2O cluster name:           H2O_started_from_R_RILITS-HWLTP_tkn816 
    H2O cluster total nodes:    1 
    H2O cluster total memory:   0.06 GB 
    H2O cluster total cores:    4 
    H2O cluster allowed cores:  2 
    H2O cluster healthy:        TRUE 

Note:  As started, H2O is limited to the CRAN default of 2 CPUs.
       Shut down and restart H2O as shown below to use all your CPUs.
           > h2o.shutdown()
           > h2o.init(nthreads = -1)

IP Address: 127.0.0.1 
Port      : 54321 
Session ID: _sid_b2e0af0f0c62cd64a8fcdee65b244d75 
Key Count : 3

我试图将 169 MB 的 csv 加载到 h2o 中。

dat.hex <- h2o.importFile('dat.csv')

引发错误，

Error in .h2o.__checkConnectionHealth() : 
  H2O connection has been severed. Cannot connect to instance at http://127.0.0.1:54321/
Failed to connect to 127.0.0.1 port 54321: Connection refused

表示内存不足error。

Question: If H2o promises loading a data set larger than its memory capacity(swap to disk mechanism as the blog quote above says), is this the correct way to load the data?

Answer 1

不久前默认禁用交换到磁盘，因为性能太差了。前沿（不是最新的稳定版）有一个启用它的标志：“--cleaner”（对于 "memory cleaner"）。
请注意，您的集群有一个非常小的内存： H2O cluster total memory: 0.06 GB 那是60MB！仅够启动 JVM，更不用说运行 H2O。如果 H2O 能在那里正常出现，我会感到惊讶，更不用说交换到磁盘了。交换仅限于单独交换数据。如果您正在尝试进行交换测试，请将您的 JVM 提高到 1 或 2 Gigs ram，然后加载总和大于此的数据集。

悬崖

在 h2o 中加载大于内存大小的数据

Loading data bigger than the memory size in h2o

java

garbage-collection

r

out-of-memory

h2o