Prepare for search, observe automatic discovery of facets
Copy the index from HDFS to the machine running the console so that it can be available for searching.
Perform the following steps.
- Start a command line session to the machine running the console.
- Log in as BigInsights administrator user, default is biadmin.
- Go to the bin directory under your accelerator install location.
- Run the command shown in Listing 2.
Listing 2. Run copyIndex utility
[user@server bin]$ ./copyIndex.sh -hdfsIndexDir=hdfs://bdvm235.svl.ibm.com:9000/GOMDADemo/output/index_out INDEX_DIR = /opt/ibm/accelerators/MDA/mda_indexes copying indexes from hdfs. Indexes successfully copied to local file system. MDA UI can be accessed at for secure install 'http://<hostname>:8080/datasearch/login.jsp'. MDA UI can be accessed at for non-secure install 'http://<hostname>:8080/datasearch/html/Search.html'.
- You are now ready to search. Open a browser instance and use the appropriate URL as described in the output of the copyIndex.sh utility.
- The search interface shows a time graph with a high-level view of
the timeframe when all the events occurred. Hovering on each of
the bars in the graph shows the number of events in each
timeframe. You can shrink down the data into a timeframe of
interest by clicking on the bar representing that timeframe. You
will be doing this in the next step.
Figure 4 shows the time graph.
Figure 4. High-level time graph
- The facets on the left are discovered based on the extracted
fields across all the data. Note the facets From and
To from the email log type.
Figure 5 shows facets across all of the data.
Figure 5. Facets across all data
The data scientists at the Sample Outdoors company noticed several facets that they would not use in their use case.
You will learn how the user interface can be configured for your use case in the Configure the user interface for your use case section of this tutorial.
- The search results list events across all of the data. Figure 6
shows the results.
Figure 6. Results listing all events
Next, you will experience the shrink down and drill down into the data.