Chapter 8. Hot and Cold Path Serving Layer in Azure

In this chapter we focus on the end goal of the lambda architecture—enabling the querying of the results of all the processing performed. To this end, we will examine the Azure services that support querying of both hot path data and cold path data by client applications and BI tools, which we will collectively refer to as the serving layer (see Figure 8-1).

The serving layer collectively deals with data from both the hot path and the cold path. It is further subdivided into a speed serving layer, which represents the subset of incrementallyprocessed hot path data that has not yet been processed by the batch techniques of the cold path, and the batch serving layer that contains the batch-processed output of the cold path. 

The main idea  behind the speed serving layer is that it supports a high degree of query flexibility—that is to say, it provides a query model enabling the client applications to ask the questions they need, be it direct lookups or more complex analytic queries. In other words, the serving layer has strong support for random reads. The serving layer also has low latency; these queries should return results in subseconds to seconds.

Figure 8-1. This chapter focuses on the serving storage components in the Azure analytics pipeline.

For the speed serving layer, because of the subsetting of the data, the actual ...

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