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is in need of maintenance is a complaint from users that their jobs are performing poorly or failing, or a page from your installation monitoring tool such as Nagios.

The NameNode is the weak point in the highly available HDFS cluster. As noted earlier, currently there are no high-availability solutions for the NameNode. The NameNode has been designed to keep multiple copies of critical data on the local machine and close in time replicas on auxiliary machines. Let s examine how it can fail.



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return oXmlDocument; } Restoring the grid layout requires a simple reversal of the preceding code. This process is shown in Listing 4-25.

Note Also, J2ME-compatible platforms exist that are not standardized by the Java Community Process,





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The NameNode keeps all of the metadata for the file system in memory to speed request services. The NameNode also serializes directory listings before sending the result to requesting applications. The memory requirements grow with the number of files and the total number of blocks in the file system. If your file system has directories with many entries and applications are scanning the directory, this can cause a large transient increase in the memory requirements for the name server. I once had a cluster that was using the Filesystem in Userspace (FUSE) contrib package to export HDFS as a read-only file system on a machine, which re-exported that file system via the Common Internet File System (CIFS) to a Windows server machine. The access patterns triggered repeated out-of-memory exceptions on the NameNode. (Using FUSE is discussed in 8.) If the DataNodes are unreliable, and they are dropping out of service and then returning to service after a gap, the NameNode will build a large queue of blocks with invalid states. This may consume very large amounts of memory if large numbers of blocks become transitorily unavailable. For this problem, addressing the DataNode reliability is the only real solution, but increasing the memory size on the NameNode can help. There are three solutions for NameNode out-of-memory problems: Increase the memory available to the NameNode, and ensure the machine has sufficient real memory to support this increase. Ensure that no directory has a large number of entries. Alter application access patterns so that there are not large numbers of directory listings.

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such as the Korean WIPI and Japanese DoJa platforms. 15 discusses these platforms in more detail. From J2ME Polish 1.3 onward, you will be able to define additional platforms in the ${polish.home}/ platforms.xml file.

For a 32-bit JVM, the maximum memory size is about 2.5GB, which will support a small HDFS cluster with a under a million files and blocks. As a general rule, pin the full memory allocation by setting the starting heap size for the JVM to the maximum heap size.

public void LoadFromXML(XmlDocument oXmlDocument) { XmlNode oXmlMainNode; if (oXmlDocument.ChildNodes.Count == 0) return; oXmlMainNode = oXmlDocument.ChildNodes[0]; this.Name = oXmlMainNode.Attributes["name"].Value; this.SortedColumn = oXmlMainNode.Attributes["sortedcolumn"].Value; if (oXmlMainNode.Attributes["sortorder"].Value != string.Empty) this.ListSortDirection = (ListSortDirection)Enum.Parse(typeof(ListSortDirection), oXmlDocument.ChildNodes[0].Attributes["sortorder"].Value, true); else this.ListSortDirection = ListSortDirection.Ascending; foreach (XmlNode oXmlNode in oXmlDocument.ChildNodes[0].ChildNodes) { GridColumn oGridColumn = new GridColumn(); oGridColumn.Name = oXmlNode.Attributes["name"].Value; oGridColumn.Visible = bool.Parse(oXmlNode.Attributes["visible"].Value); oGridColumn.DisplayIndex = int.Parse(oXmlNode.Attributes["displayindex"].Value); oGridColumn.Width = int.Parse(oXmlNode.Attributes["width"].Value); this.Columns.Add(oGridColumn); } } Here, the XML data is written to the GridInfo object, which acts as an intermediate layer between the XML and the grid control. This object allows you to support the column-selection screen shown in Figure 4-6.

Ideally, the underlying disk storage used for the NameNode s file system image (dfs.name.dir) and edit log (dfs.name.edits.dir) should be a highly reliable storage system such as a RAID 1 or RAID 5 disk array with hot spares. Even so, catastrophic failures or user errors can result in data loss.

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