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    <p>Yes, it's subassignment in R using <code>&lt;-</code> (or <code>=</code> or <code>-&gt;</code>) that makes a copy of the <em>whole</em> object. You can trace that using <code>tracemem(DT)</code> and <code>.Internal(inspect(DT))</code>, as below. The <code>data.table</code> features <code>:=</code> and <code>set()</code> assign by reference to whatever object they are passed. So if that object was previously copied (by a subassigning <code>&lt;-</code> or an explicit <code>copy(DT)</code>) then it's the copy that gets modified by reference.</p> <pre><code>DT &lt;- data.table(a = c(1, 2), b = c(11, 12)) newDT &lt;- DT .Internal(inspect(DT)) # @0000000003B7E2A0 19 VECSXP g0c7 [OBJ,NAM(2),ATT] (len=2, tl=100) # @00000000040C2288 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 1,2 # @00000000040C2250 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 11,12 # ATTRIB: # ..snip.. .Internal(inspect(newDT)) # precisely the same object at this point # @0000000003B7E2A0 19 VECSXP g0c7 [OBJ,NAM(2),ATT] (len=2, tl=100) # @00000000040C2288 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 1,2 # @00000000040C2250 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 11,12 # ATTRIB: # ..snip.. tracemem(newDT) # [1] "&lt;0x0000000003b7e2a0" newDT$b[2] &lt;- 200 # tracemem[0000000003B7E2A0 -&gt; 00000000040ED948]: # tracemem[00000000040ED948 -&gt; 00000000040ED830]: .Call copy $&lt;-.data.table $&lt;- .Internal(inspect(DT)) # @0000000003B7E2A0 19 VECSXP g0c7 [OBJ,NAM(2),TR,ATT] (len=2, tl=100) # @00000000040C2288 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 1,2 # @00000000040C2250 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 11,12 # ATTRIB: # ..snip.. .Internal(inspect(newDT)) # @0000000003D97A58 19 VECSXP g0c7 [OBJ,NAM(2),ATT] (len=2, tl=100) # @00000000040ED7F8 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 1,2 # @00000000040ED8D8 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 11,200 # ATTRIB: # ..snip.. </code></pre> <p>Notice how even the <code>a</code> vector was copied (different hex value indicates new copy of vector), even though <code>a</code> wasn't changed. Even the whole of <code>b</code> was copied, rather than just changing the elements that need to be changed. That's important to avoid for large data, and why <code>:=</code> and <code>set()</code> were introduced to <code>data.table</code>.</p> <p>Now, with our copied <code>newDT</code> we can modify it by reference :</p> <pre><code>newDT # a b # [1,] 1 11 # [2,] 2 200 newDT[2, b := 400] # a b # See FAQ 2.21 for why this prints newDT # [1,] 1 11 # [2,] 2 400 .Internal(inspect(newDT)) # @0000000003D97A58 19 VECSXP g0c7 [OBJ,NAM(2),ATT] (len=2, tl=100) # @00000000040ED7F8 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 1,2 # @00000000040ED8D8 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 11,400 # ATTRIB: # ..snip .. </code></pre> <p>Notice that all 3 hex values (the vector of column points, and each of the 2 columns) remain unchanged. So it was truly modified by reference with no copies at all.</p> <p>Or, we can modify the original <code>DT</code> by reference :</p> <pre><code>DT[2, b := 600] # a b # [1,] 1 11 # [2,] 2 600 .Internal(inspect(DT)) # @0000000003B7E2A0 19 VECSXP g0c7 [OBJ,NAM(2),ATT] (len=2, tl=100) # @00000000040C2288 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 1,2 # @00000000040C2250 14 REALSXP g0c2 [NAM(2)] (len=2, tl=0) 11,600 # ATTRIB: # ..snip.. </code></pre> <p>Those hex values are the same as the original values we saw for <code>DT</code> above. Type <code>example(copy)</code> for more examples using <code>tracemem</code> and comparison to <code>data.frame</code>.</p> <p>Btw, if you <code>tracemem(DT)</code> then <code>DT[2,b:=600]</code> you'll see one copy reported. That is a copy of the first 10 rows that the <code>print</code> method does. When wrapped with <code>invisible()</code> or when called within a function or script, the <code>print</code> method isn't called. </p> <p>All this applies inside functions too; i.e., <code>:=</code> and <code>set()</code> do not copy on write, even within functions. If you need to modify a local copy, then call <code>x=copy(x)</code> at the start of the function. But, remember <code>data.table</code> is for large data (as well as faster programming advantages for small data). We deliberately don't want to copy large objects (ever). As a result we don't need to allow for the usual 3* working memory factor rule of thumb. We try to only need working memory as large as one column (i.e. a working memory factor of 1/ncol rather than 3).</p>
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