“Last Week Tonight with John Oliver” got in its digs at tech companies on Sunday night. The show’s jab at Zillow was child’s play compared to how the host took down Facebook and the role the social giant is playing in cultures and communities overseas.

In his nearly 20-minute main story on his weekly HBO show, Oliver focused on Facebook’s impact in Myanmar in particular where internet use — and Facebook use especially — has exploded in recent years.

But the story goes beyond distracted teens and delves into serious concerns about ethnic cleansing. Certainly Facebook was not to blame for genocide in Myanmar, Olivers stressed, but the service did inflame pre-existing tensions he said. Oliver pointed to a report by independent U.N. investigators who said “Facebook has been a useful instrument for those seeking to spread hate.”

Because Oliver is a comedian, it’s not all super heavy and he does pepper his monologue with plenty of zingers:

• “Facebook: The worst place to wish happy birthday to a friend, other than a funeral.”
• Mark Zuckerberg, while explaining Facebook’s early motto “Move fast and break things,” said, “Sometimes we go too fast and we mess up a bunch of stuff and we have to fix it. And that’s cool.” Oliver asked, “Is that cool? That seems like the most reckless corporate motto since the Hindenberg company’s “Flay fast and smoke cigarettes in a big bag of hydrogen!”
• “Calling Facebook a toilet is a little unfair to toilets, because they make s*it go away, whereas Facebook retains s*it, disseminates s*it to your acquaintances, and reminds you of s*it from seven years ago, all while allowing corporations to put there s*it in front of you. There is a purity and integrity to toilets that Facebook seriously lacks.”

But Oliver gets at the seriousness of the issue in Myanmar and the tensions between different ethnic factions quite convincingly, and he wonders why so much hate speech in the country stayed up for so long on the site — which has rules against that sort of thing.

“No one should be judged by the worst things people say about them on Facebook,” Oliver argued.

Watch the full video above.

The Breville Handy Mix Scraper was the most versatile, effective mixer of any we tried, with the most functional attachments and useful features that make it a joy to use in the kitchen. With nine speeds that can toggle from powerful to gentle, it made the best cookies, sponge cake, and pizza dough in our tests. It had the most unique and intelligent design of any mixer we tried, with a built-in timer, a button to pause mixing, a light that shines into the bowl, and rubber-coated scrapers. As a bonus, it was also the simplest to clean and store compared with other mixers. We think this superior mixer is worth its relatively high cost, but the Cuisinart Power Advantage Plus 9-Speed Hand Mixer is a steadfast budget option if you want a pared-down machine for occasional tasks.

The Breville excelled in all of our tests. It was powerful enough to blend the thick cookie dough without straining, and its coated beaters helped keep all of the ingredients from climbing up the sides of the bowl. Each baked cookie was well-mixed with an even distribution of the good, chunky morsels we wanted in every bite—chewy raisins, chopped walnuts, chocolate chips, and flakes of coconut. The sponge cake it produced had an even crumb, a delicate texture, and the least air bubbles of any we baked. It was also one of the loftiest, unlike the VonShef’s cake, which sunk in the middle and at the sides. The Breville’s dough hook was even able to mix pizza dough pretty well, whacking it around to create a single ball, whereas the VonShef and the KitchenAid created stringier doughs that we had to take out of the bowl and shape on the counter. After whipping eggs and sugar for the requisite seven minutes, the Handy Mix produced just under a quart of seven-minute frosting—slightly less than the Cuisinart— but it was still fluffy, spreadable, and delicious.

Compared with those of other mixers, the Breville’s attachments stood out for their more thoughtful design and effective mixing capabilities. Rubber-coated beaters on the Breville do a better job of scraping the sides and bottom of the bowl compared with other models’ beaters, and help with noise control. “It doesn’t make a racket if you’re mixing stuff in a metal bowl,” said Lopez, who also owns this mixer. And we didn’t have to scrape the bowl with a spatula as often as with the Cuisinart when mixing our cookie dough with the beater attachment. The Breville’s two whisk attachments actually work to whip eggs for sponge cake or meringue, while we had to use the beater attachment to get similar results with all of the other mixers, which had only one whisk. In our genoise test, we found that the Breville’s whisk attachments actually worked better than the beaters at aeration (we tried both), making a more evenly baked cake.

With its clever extra features, the Breville was by far the easiest and most enjoyable mixer to use of any we tested. A screen with a built-in timer helps keep track for time-sensitive recipes, which I found especially useful when making seven-minute frosting. The timer also has a pause button, so you can stop mixing, add ingredients or scrape down your bowl, and then resume immediately without having to speed up again. You can seamlessly transition between nine speeds with a scroll wheel, similar to one an old-school computer mouse. Even though there’s nothing wrong with pressing a button, the scrolling felt easy and familiar (and made me nostalgic for pre-Apple days). The mixer also has a light at the bottom of the machine that shines into the bowl, which I used to check if the sponge cake batter had turned the pale, glossy yellow I was looking for. None of the other mixers we tested had these features, and though they’re definitely a bonus, I didn’t think they were a gimmick—they made the baking process easier overall.

Breville says that this mixer is touch-sensitive, using the company’s proprietary Beater IQ technology to adjust mixing speeds depending on which attachments you use. We didn’t notice this kicking in during testing, but the Handy Mix was sufficiently powerful to handle all of the doughs and batters we made. It seamlessly transitioned from slow to high speeds without splashing ingredients around.

This mixer was the easiest to clean and store, too. Instead of pressing a button to eject beaters, you can pull a loop to release them, which requires much less effort than with other mixers. This is a small detail, but it makes using the Breville that much easier—in contrast, I had to put my full body weight on the VonShef’s eject button to try to get the beaters out. The Handy Mix has Breville’s patented Assist Plug (found on most Breville appliances), which has a loop for your finger so that you can pull the plug out of the wall more easily. I found myself wishing that more of my kitchen appliances and home electronics had this feature.

All of the beaters are dishwasher safe, and you can easily wipe down the mixer with a damp cloth (although all hand mixers have vents—to keep the motor from overheating—that can trap food). A plastic case slides cleanly onto the base of Breville for storage, whereas you have to align the Cuisinart’s storage case with the mixer’s vents to attach one to the other. The Breville’s case neatly holds all of the beater attachments and the cord. With some other mixers, you either have to save the box the machine comes in, or store components in a bag. We like that the all-in-one system keeps the mixer’s small parts together, so that you don’t have to fumble around in a drawer for a single missing dough hook.

Epicurious also likes this mixer, and Michelle Lopez told us she uses it for many baking projects. “It’s quiet, powerful, and comes with a bunch of bells and whistles that make it great for precise baking,” she said. The Breville has a one-year limited warranty. We’ll continue to test it over time to see how it holds up.

Knowing the bits and bytes of an SQL query’s order of operations can be very valuable, as it can ease the process of writing new queries, while also being very beneficial when trying to optimize an SQL query.

If you’re looking for the short version, this is the logical order of operations, also known as the order of execution, for an SQL query:

1. FROM, including JOINs
2. WHERE
3. GROUP BY
4. HAVING
5. WINDOW functions
6. SELECT
7. DISTINCT
8. UNION
9. ORDER BY
10. LIMIT and OFFSET

But the reality isn’t that easy nor straight forward. As we said, the SQL standard defines the order of execution for the different SQL query clauses. Said that, modern databases are already challanaging that default order by applying some optimization tricks which might change the actual order of execution, though they must end up returning the same result as if they were running the query at the default execution order.

Why would they do that? Well, it can be silly if the database would first fetch all data mentioned in the FROM clause (including the JOINs), before looking into the WHERE clause and its indexes. Those tables can hold lots of data, so you can imagine what will happen if the database’s optimizer would stick to the traditional order of operations of an SQL query.

Let’s look into each of the SQL query parts according to their execution order.

FROM and JOINs

The tables specified in the FROM clause (including JOINs), will be evaluated first, to determine the entire working set which is relevant for the query. The database will merge the data from all tables, according to the JOINs ON clauses, while also fetching data from the subqueries, and might even create some temporary tables to hold the data returned from the subqueries in this clause.

In many cases though, the database’s optimizer will choose to evaluate the WHERE part first, to see which part of the working set can be left out (preferably using indexes), so it won’t inflate the data set too much if it doesn’t really have to.

WHERE clause

The WHERE clause will be the second to be evaluated, after the FROM clause. We have the working data set in place, and now we can filter the data according to the conditions in the WHERE clause.

These conditions can include references to the data and tables from the FROM clause, but cannot include any references to aliases defined in the SELECT clause, as that data and those aliases may not yet ‘exist’ in that context, as that clause wasn’t yet evaluated by the database.

Also, a common pitfall for the WHERE clause would be to try and filter out aggregated values in the WHERE clause, for example with this clause: “WHERE sum(available_stock) > 0“. This statement will fail the query execution, because aggregations will be evaluated later in the process (see the GROUP BY section below). To apply filtering condition on aggregated data, you should use the HAVING clause and not the WHERE clause.

GROUP BY clause

Now that we filtered the data set using the WHERE clause, we can aggregate the data according to one or more columns appearing in the GROUP BY clause. Grouping the data is actually splitting it to different chunks or buckets, where each bucket has one key and a list of rows that match that key. Not having a GROUP BY clause is like putting all rows in a one huge bucket.

Once you aggregate the data, you can now use aggregation functions to return a per-group value for each of the buckets. Such aggregation functions include COUNT, MIN, MAX, SUM and others.

HAVING clause

Now that we have grouped the data using the GROUP BY clause, we can use the HAVING clause to filter out some buckets. The conditions in the HAVING clause can refer to the aggregation functions, so the example which didn’t work in the WHERE clause above, will work just fine in the HAVING clause: “HAVING sum(available_stock) > 0″.

As we’ve already grouped the data, we can no longer access the original rows at this point, so we can only apply conditions to filter entire buckets, and not single rows in a bucket.

Also, as we mentioned in previous sections, aliases defined in the SELECT clause cannot be accessed in the section either, as they weren’t yet evaluated by the database (this is true in most databases).

Window functions

If you are using Window functions, this is the point where they’ll be executed. Just like the grouping mechanism, Window functions are also performing a calculation on a set of rows. The main difference is that when using Window functions, each row will keep its own identity and won’t be grouped into a bucket of other similar rows.

Window functions can only be used in either the SELECT or the ORDER BY clause. You can use aggregation functions inside the Window functions, for example:

SUM(COUNT(*)) OVER ()

SELECT clause

Now that we are done with discarding rows from the data set and grouping the data, we can select the data we want to be fetched from the query to the client side. You can use column names, aggregations and subqueries inside the SELECT clause. Keep in mind that if you’re using a reference to an aggregation function, such as COUNT(*) in the SELECT clause, it’s merely a reference to an aggregation which already occurred when the grouping took place, so the aggregation itself doesn’t happen in the SELECT clause, but this is only a reference to its result set.

DISTINCT keyword

The syntax of the DISTINCT keyword is a bit confusing, because the keyword takes its place before the column names in the SELECT clause. But, the actual DISTINCT operation takes place after the SELECT. When using the DISTINCT keyword, the database will discard rows with duplicate values from the remaining rows left after the filtering and aggregations took place.

UNION keyword

The UNION keyword combines the result sets of two queries into one result set. Most databases will allow you to choose between UNION DISTINCT (which will discard duplicate rows from the combined result set) or UNION ALL (which just combines the result sets without applying any duplication check).

You can apply sorting (ORDER BY) and limiting (LIMIT) on the UNION’s result set, the same way you can apply it on a regular query.

ORDER BY clause

Sorting takes place once the database has the entire result set ready (after filtering, grouping, duplication removal). Once we have that, the database can now sort the result set using columns, selected aliases, or aggregation functions, even if they aren’t part of the selected data. The only exception is when using the DISTINCT keyword, which prevents sorting by a non-selected column, as in that case the result set’s order will be undefined.

You can choose to sort the data using a descending (DESC) order or an ascending (ASC) order. The order can be unique for each of the order parts, so the following is valid: ORDER BY firstname ASC, age DESC

LIMIT and OFFSET

In most use cases (excluding a few like reporting), we would want to discard all rows but the first X rows of the query’s result. The LIMIT clause, which is executed after sorting, allows us to do just that. In addition, you can choose which row to start fetching the data from and how many to exclude, using a combination of the LIMIT and OFFSET keywords. The following example will fetch 50 rows starting row #100: LIMIT 50 OFFSET 100