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In the following example, the argument set -splitSample 1000 10 will sample a total of 1,000 input records out of no more than 10 input splits bin/hadoop jar hadoop-0190-corejar orgapachehadoopmapredlibInputSampler -inFormat orgapachehadoopmapredKeyValueTextInputFormat -keyClass orgapachehadoopioText -r 15 -splitSample 1000 10 csvin csvout If there are 10 or more input splits, each of which has more than 100 records, the first 100 records from each input split will be used for samples The input is loaded from the directory csvin, and is parsed by the KeyValueTextInputFormat class The range file is written to csvout, and the argument set -r 15 sets up the output for a job with 15 output partitions The input splits are examined in the order in which they are returned by InputFormat.

The next example takes 1,000 samples from roughly 10 input splits The input splits are sampled in a random order, and the records from each split read are sequentially bin/hadoop jar hadoop-0190-corejar orgapachehadoopmapredlibInputSampler -inFormat orgapachehadoopmapredKeyValueTextInputFormat -keyClass orgapachehadoopioText -r 15 -splitRandom 1 1000 10 csvin csvout Each record has a 01% chance of being selected The -splitRandom 1 1000 10 argument set specifies the percentage, the total samples, and the maximum splits to sample If the 1,000 samples are not selected after processing the recommended number of splits, more splits will be sampled The index is set up for 15 reduce tasks, and the input comes from csvin The index is written to csvout The splits to examine are selected randomly In the final example, the argument set -splitInterval .

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One very common request for geolocation data is to show a user s position on a map, such as the popular Google Maps service. In fact, this is so popular that Google itself built support for HTML5 Geolocation into its user interface. Simply press the Show My Location button (see Figure 4-5); Google Maps will use the Geolocation API (if it is available) to determine and display your location on the map.

The component element is used to map classes that will be represented as extra columns within a table describing some other class. We have already discussed how components fit in as a compromise between full entity types and mere value types. The <component> element can take the attributes listed in Table 6-7. Table 6-7. The <component> Attributes

01 10 will examine no more than 10 input splits and take one record in 100 from each split..

bin/hadoop jar hadoop-0.19.0-core.jar org.apache.hadoop.mapred.lib.InputSampler -inFormat org.apache.hadoop.mapred.KeyValueTextInputFormat -keyClass org.apache.hadoop.io.Text -r 15 -splitInterval .01 10 csvin csvout The frequency parameter defines how many records will be sampled. For a frequency of 0.1, as in this example, one record in 10 will be used. For a frequency of 0.01, one record in 100 will be used. The index is set up for 15 reduce tasks. The input comes from csvin, and the index is written to csvout.

Figure 4-5. Google Map s Show My Location button However, it is also possible to do this yourself. Although the Google Map API is beyond the scope of this book, it has (not coincidentally) been designed to take decimal latitude and longitude locations. Therefore, you can easily pass the results of your position lookup to the Google Map API, as shown in Listing 4-18. You can read more on this subject in Beginning Google Maps Applications, Second Edition (Apress, 2010).

Once an index is generated, a job may be set up to use the TotalOrderPartitioner and the index. Three configuration settings are required for this to work: The partitioner must be set to TotalOrderPartitioner in the JobConf object via conf.se tPartitionerClass(TotalOrderPartitioner). The partitioning index must be specified via the configuration key total.order.partitioner.path: conf.set("total.order.partitioner.path", "csvout"); The sort type for the keys must also be specified. If the binary representation of the keys is the correct sorting, the Boolean field total.order.partitioner.natural.order should be set to true in the configuration. If the binary representation of the keys is not the correct sort, the Boolean field total.order.partitioner.natural.order must be set to false. This Boolean field is set as follows: conf.setBoolean("total.order.partitioner.natural.order"); If the binary representation of the key is the correct sort order, a binary trie (an ordered tree structure; see http://en.wikipedia.org/wiki/Trie) will be constructed and used for searching; otherwise, a binary search based on the output key comparator will be used. Here s an example of how to put all this together: TotalOrderPartitioner.setPartitionFile(conf,"csvout"); conf.setPartitionerClass(TotalOrderPartitioner.class); conf.set("total.order.partitioner.natural.order",false); conf.setNumReduceTasks (15); In this example, csvin is the input file, and csvout is the index file. The csvout file was set up for 15 reduce tasks, and requires the comparator rather than binary comparison.

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