Hbase write ahead log

Tweet I cleared the Cloudera Certified Hadoop Developer CCD — examination and I just wanted to list down a few suggestions for those wanting to appear for the same. If you are here looking for questions that are part of the CCD test, you have come to the wrong place.

Hbase write ahead log

In my previous post we had a look at the general storage architecture of HBase. This post explains how the log works in detail, but bear in mind that it describes the current version, which is 0.

I will address the various plans to improve the log for 0. For the term itself please read here. This is important in case something happens to the primary storage. So if the server crashes it can effectively replay that log to get everything up to where the server should have been just before the crash.

It also means that if writing the record to the WAL fails the whole operation must be considered a failure.

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Let"s look at the high level view of how this is done in HBase. First the client initiates an action that modifies data. This is currently a call to put Putdelete Delete and incrementColumnValue abbreviated as "incr" here at times.

And that also pretty much describes the write-path of HBase. Eventually when the MemStore gets to a certain size or after a specific time the data is asynchronously persisted to the file system.

In between that timeframe data is stored volatile in memory. We have a look now at the various classes or "wheels" working the magic of the WAL. First up is one of the main classes of this contraption. What you may have read in my previous post and is also illustrated above is that there is only one instance of the HLog class, which is one per HRegionServer.

It is what is called when the above mentioned modification methods are invoked One thing to note here is that for performance reasons there is an option for putdeleteand incrementColumnValue to be called with an extra parameter set: If you invoke this method while setting up for example a Put instance then the writing to WAL is forfeited!

That is also why the downward arrow in the big picture above is done with a dashed line to indicate the optional step.

hbase write ahead log

By default you certainly want the WAL, no doubt about that. But say you run a large bulk import MapReduce job that you can rerun at any time. You gain extra performance but need to take extra care that no data was lost during the import.

The choice is yours. Another important feature of the HLog is keeping track of the changes. This is done by using a "sequence number".

It uses an AtomicLong internally to be thread-safe and is either starting out at zero - or at that last known number persisted to the file system. So at the end of opening all storage files the HLog is initialized to reflect where persisting has ended and where to continue.

You will see in a minute where this is used. The image to the right shows three different regions.In CDH and higher, you can configure the preferred HDFS storage policy for HBase's write-ahead log (WAL) replicas.

This feature allows you to tune HBase's use of SSDs to your available resources and the demands of your workload. Turning this off means that the RegionServer will not write the Put to the Write Ahead Log When writing a lot of data to an HBase table from a MR job (e.g., with TableOutputFormat), and specifically where Puts are being emitted from the Mapper, skip the Reducer step.

When a Reducer step is used, all of the output (Puts) from the . There is a lot of excitement about Big Data and a lot of confusion to go with it. This article provides a working definition of Big Data and then works through a series of examples so you can have a first-hand understanding of some of the capabilities of Hadoop, the leading .

hbase write ahead log

Creates a new table. The HBase table and any column families referenced are created if they don't already exist. All table, column family and column names are uppercased unless they are double quoted in which case they are case sensitive. The HBase root directory is stored in Amazon S3, including HBase store files and table metadata.

This data is persistent outside of the cluster, available across Amazon EC2 Availability Zones, and you don't need to recover using snapshots or other methods.

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NoSQL Databases: a Survey and Decision Guidance – Baqend Blog