Exam DP-203 topic 1 question 19 discussion

Round-Robin Heap None

Round-robin - this is the simplest distribution model, not great for querying but fast to process Heap - no brainer when creating staging tables No partitions - this is a staging table, why add effort to partition, when truncated daily?

as per Microsoft document Load to a staging table To achieve the fastest loading speed for moving data into a data warehouse table, load data into a staging table. Define the staging table as a heap and use round-robin for the distribution option. Consider that loading is usually a two-step process in which you first load to a staging table and then insert the data into a production data warehouse table. If the production table uses a hash distribution, the total time to load and insert might be faster if you define the staging table with the hash distribution. Loading to the staging table takes longer, but the second step of inserting the rows to the production table does not incur data movement across the distributions.

Answer: Round-Robin (1), Heap (2), None (3). Within this doc: https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/develop-tables-overview #1. Search for “Use round-robin for the staging table.” #2. Search for: “A heap table can be especially useful for loading data, such as a staging table,…” Within this doc: https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-partition?context=/azure/synapse-analytics/context/context #3. Partitioning by date is useful when stage destination has data because you can hide the inserting data’s new partition (to keep users from hitting it), complete the load and then unhide the new partition. However, in this question it states, “the table will be truncated before each daily load”, so, it appears it’s a true Staging table and there are no users with access, no existing data, and I see no reason to have a Date partition. To me, such a partition would do nothing but slow the load.

Since it's the staging table, the main focus should be minimizing the load time, as noted in the question. Heap table does not have any index and it's the fastest option for loading large amounts of data. Using a round-robin distribution will help to evenly distribute the data across all the distributions, further reducing the load time. As the data is truncated before each load, partitioning is not necessary, so it is best to choose None. Round-robin Heap None

Distribution: Round Robin Indexing: Clustered Columnstore Partitioning: Date The recommended configuration for a staging table that will be loaded daily with approximately 1 million rows of data and truncated before each load is to use a round robin distribution, a clustered columnstore index, and date-based partitioning. Round robin distribution will evenly distribute the data across nodes, reducing the load time. Clustered columnstore index provides efficient compression and supports fast bulk load operations. Date-based partitioning will allow for easy archiving and maintenance of the table.

Round-Robing, Heap, None. The question is to configure the staging table. According to the conditions, "The solution must minimize how long it takes to load the data to the staging table." Therefore, loading time is the most essential condition here. According to Microsoft documentation at https://learn.microsoft.com/en-us/azure/synapse-analytics/sql/develop-tables-overview Distribution: A round-robin table distributes table rows evenly across all distributions. The rows are distributed randomly. Loading data into a round-robin table is fast. But, queries can require more data movement than the other distribution methods. Indexing: A heap table can be especially useful for loading transient data, such as a staging table, which is transformed into a final table. Partitioning: None. Since the table is truncated before each daily load, we can not benefit of partitioning to drop date ranges.

1 --> REPLICATED Since table has always 1mln rows (it is a small staging table, loaded in truncate-insert everyday!) Also Round-Robin is wrong, since 1mln/60nodes = almost 17k rows per compute node, which is a unrecommended situation. You haven't data enough to choose round-robin. 2 --> HEAP Why do you have to choose clustered columnstore index? This is not a big table. 3 --> None Since you haven't data enough to create a efficient partition. It's more convenient to have only one partition in this case.

Copilot Sent by Copilot: To optimize the loading process for your staging table in Azure Synapse, here are the recommended configurations: Distribution: Use Round-robin distribution. This method evenly distributes the data across all distributions, which helps in achieving balanced data loading and minimizes data skew. Indexing: Use Heap. Since the table will be truncated before each load, using a heap (a table without a clustered index) will speed up the data loading process as it avoids the overhead of maintaining indexes during the load. Partitioning: Do not partition the staging table. Partitioning can add overhead to the data loading process. Since the table is truncated daily, partitioning is not necessary and can be avoided to keep the load process efficient. These configurations will help minimize the time it takes to load data into the staging table.

RR Heap Date

Round robin Heap None

RR Heap None

Round-Robin Heap None

Round-Robin Heap None

Round-Robin Heap None

Never ever use date partioning with hash distribution. The correct answer is: Round robin, Heap and None

Round-robin - this is the simplest distribution model, not great for querying but fast to process Heap - no brainer when creating staging tables No partitions - this is a staging table