Can an H2O cluster run out of memory?
H2O supports import of partitioned tables that use different storage formats for different partitions; however, in some cases (for example, a large number of small partitions), H2O may run out of memory during the import, even though the final data will easily fit in the memory allocated to the H2O cluster.
Table of Contents
What is the minimum memory size for H2O in Java?
This amount depends on the version of Java, but will generally be 25% of the physical memory of the machine. min_mem_size – (Optional) A character string specifying the minimum size, in bytes, of the memory allocation pool for H2O.
What kind of data can I upload to H2O?
Whether you’re importing data, loading data, or retrieving data from HDFS or S3, make sure your data is compatible with H2O. H2O currently supports the following file types: CSV files (delimited, UTF-8 only) (including GZipped CSV) Avro version 1.8.0 (no multifile parsing or column type modification)
How can I import data to my H2O cluster?
Data hosted on the Internet can be imported into H2O by specifying the URL. For more information, see Importing a file. Various data sources can be accessed through an HDFS API. In this case, a library that provides access to a data source must be passed on a command line when H2O is started.
When to use swap to disk on H2O?
Question: If H2o promises to load a dataset larger than its memory capacity (swap-to-disk mechanism as the above blog quote says), is this the correct way to load the data? Swap-to-disk was disabled by default a while back, because performance was so poor.
How big is the memory for H2O in R?
init(max_mem_size = ’60m’) # allocating 60mb for h2o, R running on a 8GB RAM machine gives
When does Java load data larger than memory size?
The H2o blog mentions: A note on Bigger Data and GC: We do a user-mode switch to disk when the Java heap gets too full, ie it’s 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 drive allows.
When does the H2O executable not start?
If an existing connection is detected, R does not start H2O. forceDL: (Optional) A logical value indicating whether to force the download of the H2O executable.
How can I upload data to my H2O cluster?
Data from a local machine can be loaded into H2O via a client push. For more information, see Uploading a file. Data hosted on the Internet can be imported into H2O by specifying the URL. For more information, see Importing a file. Various data sources can be accessed through an HDFS API.
How does H2O read data from the Hive table?
H2O can read the metadata from the Hive table in two ways: through direct Metastore access or through JDBC. Note: When ingesting Hive data into Hadoop, direct import from Hive is preferred over using the Hive 2 JDBC driver. The user running H2O must have read access to Hive and the files it manages.
What type of database is used for H2O?
Relational databases that include a Java Database Connectivity (JDBC) driver can be used as a data source for machine learning in H2O. Currently supported SQL databases are MySQL, PostgreSQL, MariaDB, Netezza, Amazon Redshift, Teradata, and Hive.