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7:[["$","meta","0",{"name":"viewport","content":"width=device-width, initial-scale=1"}],["$","meta","1",{"charSet":"utf-8"}],["$","title","2",{"children":"Parallelizing queries | Deephaven"}],["$","meta","3",{"name":"description","content":"Deephaven supports using multiple processors to speed up query evaluation. The extent to which Deephaven employs\nmultiple processors depends on both the phase o..."}],["$","meta","4",{"name":"compiledAt","content":"2025-10-28T19:27:43.430Z"}],["$","meta","5",{"name":"inkeep:version","content":"core-groovy-current"}],["$","meta","6",{"name":"inkeep:docusaurus_tag","content":"core-groovy-current"}],["$","link","7",{"rel":"icon","href":"/favicon.ico","type":"image/x-icon","sizes":"16x16"}],["$","link","8",{"rel":"icon","href":"/icon.svg?ea04df7589c797b6","type":"image/svg+xml","sizes":"any"}],["$","meta","9",{"name":"next-size-adjust"}]]
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2:[["$","$L2d",null,{"toc":[{"value":"Query initialization and updates","href":"#query-initialization-and-updates","depth":2,"numbering":[1,1],"parent":"root"},{"value":"Query initialization","href":"#query-initialization","depth":3,"numbering":[1,1,1],"parent":"root"},{"value":"Query updates","href":"#query-updates","depth":3,"numbering":[1,1,2],"parent":"root"},{"value":"Parallelizing queries","href":"#parallelizing-queries","depth":2,"numbering":[1,2],"parent":"root"},{"value":"Parallelizing query initialization","href":"#parallelizing-query-initialization","depth":3,"numbering":[1,2,1],"parent":"root"},{"value":"Parallelizing query updates","href":"#parallelizing-query-updates","depth":3,"numbering":[1,2,2],"parent":"root"},{"value":"Controlling Concurrency for select, update and where","href":"#controlling-concurrency-for-select-update-and-where","depth":3,"numbering":[1,2,3],"parent":"root"},{"value":"Managing thread pool sizes","href":"#managing-thread-pool-sizes","depth":3,"numbering":[1,2,4],"parent":"root"},{"value":"Related documentation","href":"#related-documentation","depth":3,"numbering":[1,2,5],"parent":"root"}],"children":["$","ul",null,{"children":[["$","li",null,{"children":["$","a",null,{"href":"https://github.com/deephaven/deephaven-core/issues/new?title=Docs%20feedback%20on%20%2Fcore%2Fgroovy%2Fdocs%2Fconceptual%2Fquery-engine%2Fparallelization.md","children":"Question? Give us feedback ↗"}]}],["$","li",null,{"children":["$","a",null,{"href":"https://github.com/deephaven/deephaven-core/tree/main/docs/groovy/conceptual/query-engine/parallelization.md","children":"Edit this page on GitHub ↗"}]}],["$","li",null,{"children":["$","a",null,{"href":"#top","children":"↑ Back to top"}]}],false]}]}],["$","article",null,{"children":["$","div",null,{"className":"markdown","children":["$undefined",["$","h1",null,{"children":"Parallelizing queries"}],[["$","p",null,{"children":"Deephaven supports using multiple processors to speed up query evaluation. The extent to which Deephaven employs\nmultiple processors depends on both the phase of operation and the query itself."}],"\n",["$","h2",null,{"id":"query-initialization-and-updates","children":["Query initialization and updates",["$","$Lf",null,{"href":"#query-initialization-and-updates","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"icon icon-link"}]}]]}],"\n",["$","p",null,{"children":"When considering Deephaven query performance, there are two distinct phases to consider: initialization and updates."}],"\n",["$","h3",null,{"id":"query-initialization","children":["Query initialization",["$","$Lf",null,{"href":"#query-initialization","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"icon icon-link"}]}]]}],"\n",["$","p",null,{"children":["Every table operation method — ",["$","$Lf",null,{"href":"../../../reference/table-operations/filter/where","children":["$","code",null,{"children":".where"}]}],",\n",["$","$Lf",null,{"href":"../../../reference/table-operations/select/update","children":["$","code",null,{"children":".update"}]}],",\n",["$","$Lf",null,{"href":"../../../reference/table-operations/join/natural-join","children":["$","code",null,{"children":".naturalJoin"}]}],", etc. — undergoes an ",["$","em",null,{"children":"initialization"}]," phase\nwhen the method is called. Initialization produces a result table based on the data in the source table. For example,\nwith a 100,000-row table called ",["$","code",null,{"children":"myTable"}],", running ",["$","code",null,{"children":"myTable.update(\"X = random()\")"}]," will run the ",["$","code",null,{"children":"random()"}]," method\n100,000 times (once per row)."]}],"\n",["$","p",null,{"children":["If an operation's source table is\n",["$","$Lf",null,{"href":"https://deephaven.io/core/javadoc/io/deephaven/engine/table/impl/BaseTable.html#isRefreshing()","children":"refreshing"}],",\nthen initialization will create a new node in the ",["$","$Lf",null,{"href":"../../dag","children":"update graph"}]," as well."]}],"\n",["$","h3",null,{"id":"query-updates","children":["Query updates",["$","$Lf",null,{"href":"#query-updates","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"icon icon-link"}]}]]}],"\n",["$","p",null,{"children":["After initialization, the Periodic Update Graph (UG) monitors source tables for changes and process ",["$","em",null,{"children":"updates"}]," to any\ntable. For example, if 25,000 rows are added to ",["$","code",null,{"children":"myTable"}],", the UG will run the ",["$","code",null,{"children":"random()"}]," method 25,000\nmore times, calculating the value of column ",["$","code",null,{"children":"X"}]," for each of the new rows."]}],"\n",["$","h2",null,{"id":"parallelizing-queries","children":["Parallelizing queries",["$","$Lf",null,{"href":"#parallelizing-queries","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"icon icon-link"}]}]]}],"\n",["$","h3",null,{"id":"parallelizing-query-initialization","children":["Parallelizing query initialization",["$","$Lf",null,{"href":"#parallelizing-query-initialization","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"icon icon-link"}]}]]}],"\n",["$","p",null,{"children":["Deephaven is a column-oriented query engine — it focuses on handling data one column at a time, instead of one row at\na time like many traditional databases. Since\nDeephaven ",["$","$Lf",null,{"href":"/core/javadoc/io/deephaven/engine/table/ColumnSource.html","children":"column sources"}]," support random\naccess to data, different segments of a column can be processed in parallel. When possible, the Deephaven\nengine will do this automatically, based on the number of threads in the Operation Initialization Thread Pool."]}],"\n",["$","h3",null,{"id":"parallelizing-query-updates","children":["Parallelizing query updates",["$","$Lf",null,{"href":"#parallelizing-query-updates","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"icon icon-link"}]}]]}],"\n",["$","p",null,{"children":["As with query initialization, some operations can process different sections of a column in parallel. However, update\nprocessing can also be parallelized across independent nodes of the ",["$","$Lf",null,{"href":"../../dag","children":"DAG"}],". Parallel processing\nof updates depends on the size of the Periodic Update Graph Thread Pool."]}],"\n",["$","p",null,{"children":"Consider the following hypothetical example:"}],"\n",["$","$2e",null,{"children":"$L2f"}],"\n",["$","p",null,{"children":["The three intermediate tables ",["$","code",null,{"children":"my_table_updated"}],", ",["$","code",null,{"children":"my_table_filtered1"}]," and ",["$","code",null,{"children":"my_table_filtered2"}]," all depend on only one\nother table — the original ",["$","code",null,{"children":"my_table"}],". Since they are independent of each other, when ",["$","code",null,{"children":"my_table"}]," is updated with new or\nmodified rows it is possible for the query engine to process the new rows into ",["$","code",null,{"children":"my_table_updated"}],", ",["$","code",null,{"children":"my_table_filtered1"}],"\nand ",["$","code",null,{"children":"my_table_filtered2"}]," at the same time. However, since ",["$","code",null,{"children":"merged_tables"}]," depends on those three tables, the query\nengine cannot update the result of the ",["$","$Lf",null,{"href":"../../../reference/table-operations/merge/merge","children":["$","code",null,{"children":"merge"}]}]," operation until after\nthe ",["$","code",null,{"children":"update()"}]," and ",["$","code",null,{"children":"where()"}],"s for those three tables have been processed."]}],"\n",["$","h3",null,{"id":"controlling-concurrency-for-select-update-and-where","children":["Controlling Concurrency for ",["$","code",null,{"children":"select"}],", ",["$","code",null,{"children":"update"}]," and ",["$","code",null,{"children":"where"}],["$","$Lf",null,{"href":"#controlling-concurrency-for-select-update-and-where","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"icon icon-link"}]}]]}],"\n",["$","p",null,{"children":["The ",["$","code",null,{"children":"select"}],", ",["$","code",null,{"children":"update"}],", and ",["$","code",null,{"children":"where"}]," operations can parallelize within a single where clause or column expression. This can greatly improve throughput by using multiple threads to read existing columns or compute functions. Deephaven can only parallelize an expression if it is ",["$","em",null,{"children":"stateless"}],", meaning it does not depend on any mutable external inputs or the order in which rows are evaluated. Many operations, such as String manipulation or arithmetic on one or more input columns are stateless. By default, the Deephaven engine assumes that expressions are not stateless. For ",["$","code",null,{"children":"select"}]," and ",["$","code",null,{"children":"update"}],", you can change the configuration property ",["$","code",null,{"children":"QueryTable.statelessSelectByDefault"}]," to ",["$","code",null,{"children":"true"}]," to make columns stateless by default. For filters, change the property ",["$","code",null,{"children":"QueryTable.statelessFiltersByDefault"}],"."]}],"\n",["$","div",null,{"className":"markdown-alert markdown-alert-note","children":[["$","p",null,{"className":"markdown-alert-title","children":[["$","svg",null,{"xmlns":"http://www.w3.org/2000/svg","width":"16","height":"16","fill":"currentColor","viewBox":"0 0 16 16","children":[["$","path",null,{"d":"M8 15A7 7 0 1 1 8 1a7 7 0 0 1 0 14m0 1A8 8 0 1 0 8 0a8 8 0 0 0 0 16"}],["$","path",null,{"d":"m8.93 6.588-2.29.287-.082.38.45.083c.294.07.352.176.288.469l-.738 3.468c-.194.897.105 1.319.808 1.319.545 0 1.178-.252 1.465-.598l.088-.416c-.2.176-.492.246-.686.246-.275 0-.375-.193-.304-.533zM9 4.5a1 1 0 1 1-2 0 1 1 0 0 1 2 0"}]]}],"Note"]}],"\n",["$","p",null,{"children":"\nIn a future version of Deephaven, filters and selectables will be stateless by default."}],"\n"]}],"\n",["$","p",null,{"children":["The ",["$","$Lf",null,{"href":"https://docs.deephaven.io/core/javadoc/io/deephaven/api/ConcurrencyControl.html","children":["$","code",null,{"children":"ConcurrencyControl"}]}]," interface allows you to control the behavior of ",["$","$Lf",null,{"href":"https://docs.deephaven.io/core/javadoc/io/deephaven/api/filter/Filter.html","children":["$","code",null,{"children":"Filter"}]}]," (where clause) and ",["$","$Lf",null,{"href":"https://docs.deephaven.io/core/javadoc/io/deephaven/api/Selectable.html","children":["$","code",null,{"children":"Selectable"}]}]," (column formula) objects."]}],"\n",["$","p",null,{"children":["ConccurencyControl cannot be applied to Selectables passed to ",["$","code",null,{"children":"view"}]," or ",["$","code",null,{"children":"updateView"}],". The ",["$","code",null,{"children":"view"}]," and ",["$","code",null,{"children":"updateView"}]," operations compute results on demand, and therefore cannot enforce ordering constraints."]}],"\n",["$","p",null,{"children":["To explicitly mark a Selectable or Filter as stateful, use the ",["$","code",null,{"children":"withSerial"}]," method."]}],"\n",["$","ul",null,{"children":["\n",["$","li",null,{"children":"A serial Filter cannot be reordered with respect to other Filters. Every input row to a stateful Filter is evaluated in order."}],"\n",["$","li",null,{"children":"When a Selectable is serial, then every row for that column is evaluated in order."}],"\n",["$","li",null,{"children":["For Selectables, additional ordering constraints are controlled by the value of the ",["$","code",null,{"children":"QueryTable.SERIAL_SELECT_IMPLICIT_BARRIERS"}],". This is set by the property ",["$","code",null,{"children":"QueryTable.serialSelectImplicitBarriers"}],". The default value is the inverse of ",["$","code",null,{"children":"QueryTable.statelessSelectByDefault"}],". When ",["$","code",null,{"children":"Selectables"}]," are stateless by default, no implicit barriers are added (i.e., ",["$","code",null,{"children":"QueryTable.SERIAL_SELECT_IMPLICIT_BARRIERS"}]," is false). When ",["$","code",null,{"children":"Selectables"}]," are stateful by default, then implicit barriers are added (i.e. ",["$","code",null,{"children":"QueryTable.SERIAL_SELECT_IMPLICIT_BARRIERS"}]," is true)."]}],"\n",["$","li",null,{"children":["If ",["$","code",null,{"children":"QueryTable.SERIAL_SELECT_IMPLICIT_BARRIERS"}]," is false, no additional ordering between expressions is imposed. As with every ",["$","code",null,{"children":"select"}]," or ",["$","code",null,{"children":"update"}]," call, if column B references column A, then the necessary inputs to column B from column A are evaluated before column B is evaluated. To impose further ordering constraints, use barriers."]}],"\n",["$","li",null,{"children":["If ",["$","code",null,{"children":"QueryTable.SERIAL_SELECT_IMPLICIT_BARRIERS"}]," is true, then a serial selectable is an absolute barrier with respect to all other serial selectables. This prohibits serial selectables from being evaluated concurrently, permitting them to access global state. Selectables that are not serial may be reordered with respect to a serial selectable."]}],"\n"]}],"\n",["$","p",null,{"children":["Filters and Selectables may declare a ",["$","em",null,{"children":"barrier"}],". A barrier is an opaque object (compared using reference equality) that is used to mark a particular Filter or Selectable. Subsequent Filters or Selectables may respect a previously declared barrier. If a Filter respects a barrier, that Filter cannot begin evaluation until the Filter which declares the barrier has been completely evaluated. Similarly, if a Selectable respects a barrier, then it cannot begin evaluation until the Selectable which declared the barrier has been completely evaluated."]}],"\n",["$","p",null,{"children":["In this code block, two columns reference the AtomicInteger ",["$","code",null,{"children":"a"}],":"]}],"\n",["$","$2e",null,{"children":"$L30"}],"\n",["$","$L31",null,{"objectsFile":"/snapshots/ee86bb51e5ef19dfe2b03874ad0290e0.json","order":"null","path":"https://d2qmtmpk475t23.cloudfront.net/deephaven/deephaven-core/groovy/docs/main"}],"\n",["$","p",null,{"children":["Deephaven's default behavior is to treat both ",["$","code",null,{"children":"A"}]," and ",["$","code",null,{"children":"B"}]," statefully, therefore the table is equivalent to:"]}],"\n",["$","$2e",null,{"children":"$L32"}],"\n",["$","$L31",null,{"objectsFile":"/snapshots/6a7c61c6fe19f96f4c830e665473e1a7.json","order":"null","path":"https://d2qmtmpk475t23.cloudfront.net/deephaven/deephaven-core/groovy/docs/main"}],"\n",["$","p",null,{"children":["However, when the columns are stateless, then the rows from either column can be evaluated in any order. To indicate that ",["$","code",null,{"children":"A"}]," must be evaluated before ",["$","code",null,{"children":"B"}],", we can use a barrier:"]}],"\n",["$","$2e",null,{"children":"$L33"}],"\n",["$","$L31",null,{"objectsFile":"/snapshots/fffef25f7086f2f12fba038f2dd70c05.json","order":"null","path":"https://d2qmtmpk475t23.cloudfront.net/deephaven/deephaven-core/groovy/docs/main"}],"\n",["$","p",null,{"children":["Similarly, we can prevent values of A from appearing out of order using ",["$","code",null,{"children":"withSerial"}],":"]}],"\n",["$","$2e",null,{"children":"$L34"}],"\n",["$","$L31",null,{"objectsFile":"/snapshots/dbf2a5add834caa257d34d65b0f2039d.json","order":"null","path":"https://d2qmtmpk475t23.cloudfront.net/deephaven/deephaven-core/groovy/docs/main"}],"\n",["$","h3",null,{"id":"managing-thread-pool-sizes","children":["Managing thread pool sizes",["$","$Lf",null,{"href":"#managing-thread-pool-sizes","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"icon icon-link"}]}]]}],"\n",["$","p",null,{"children":"The maximum parallelism of query initialization and update processing is determined by the Operation Initialization\nThread Pool and the Periodic Update Graph Thread Pool. The size of these values is controlled using the properties\ndescribed in the table below:"}],"\n",["$","div",null,{"className":"table-container","children":["$","table",null,{"children":[["$","thead",null,{"children":["$","tr",null,{"children":[["$","th",null,{"children":"Thread Pool Property"}],["$","th",null,{"children":"Default Value"}],["$","th",null,{"children":"Description"}]]}]}],["$","tbody",null,{"children":[["$","tr",null,{"children":[["$","td",null,{"children":"OperationInitializationThreadPool.threads"}],["$","td",null,{"children":"-1"}],["$","td",null,{"children":"Determines the number of threads available for parallel processing of initialization operations."}]]}],["$","tr",null,{"children":[["$","td",null,{"children":"PeriodicUpdateGraph.updateThreads"}],["$","td",null,{"children":"-1"}],["$","td",null,{"children":"Determines the number of threads available for parallel processing of the Periodic Update Graph refresh cycle."}]]}]]}]]}]}],"\n",["$","p",null,{"children":["Setting either of these properties to ",["$","code",null,{"children":"-1"}]," instructs Deephaven to use all available processors. The number of available\nprocessors is retrieved from the Java Virtual Machine at Deephaven startup,\nusing ",["$","$Lf",null,{"href":"https://docs.oracle.com/en/java/javase/11/docs/api/java.base/java/lang/Runtime.html#availableProcessors()","children":"Runtime.availableProcessors()"}],"."]}],"\n",["$","h3",null,{"id":"related-documentation","children":["Related documentation",["$","$Lf",null,{"href":"#related-documentation","aria-hidden":"true","tabIndex":"-1","children":["$","span",null,{"className":"icon icon-link"}]}]]}],"\n",["$","ul",null,{"children":["\n",["$","li",null,{"children":["$","$Lf",null,{"href":"../../dag","children":"Deephaven’s Directed-Acyclic-Graph (DAG)"}]}],"\n",["$","li",null,{"children":["$","$Lf",null,{"href":".././engine-locking","children":"Multithreading: Synchronization, locks, and snapshots"}]}],"\n"]}]]]}]}]]
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36:Tb8f,<pre class="shiki shiki-themes github-light github-dark" style="background-color:#fff;--shiki-dark-bg:#24292e;color:#24292e;--shiki-dark:#e1e4e8" tabindex="0"><code><span class="line"><span style="color:#6A737D;--shiki-dark:#6A737D">// Retrieve a live table:</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">my_table </span><span style="color:#D73A49;--shiki-dark:#F97583">=</span><span style="color:#24292E;--shiki-dark:#E1E4E8"> get_my_kafka_feed_table()</span></span>
<span class="line"></span>
<span class="line"><span style="color:#6A737D;--shiki-dark:#6A737D">// Run several independent query operations on 'my_table':</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">my_table_updated </span><span style="color:#D73A49;--shiki-dark:#F97583">=</span><span style="color:#24292E;--shiki-dark:#E1E4E8"> my_table</span><span style="color:#D73A49;--shiki-dark:#F97583">.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">update(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"MyCalculation = computeValue(Col1, Col2, ColRed, ColBlue)"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">)</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">my_table_filtered1 </span><span style="color:#D73A49;--shiki-dark:#F97583">=</span><span style="color:#24292E;--shiki-dark:#E1E4E8"> my_table</span><span style="color:#D73A49;--shiki-dark:#F97583">.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">where(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"ColX &#x3C; 10000"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">)</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">my_table_filtered2 </span><span style="color:#D73A49;--shiki-dark:#F97583">=</span><span style="color:#24292E;--shiki-dark:#E1E4E8"> my_table</span><span style="color:#D73A49;--shiki-dark:#F97583">.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">where(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"ColY > ColZ"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">)</span></span>
<span class="line"></span>
<span class="line"><span style="color:#6A737D;--shiki-dark:#6A737D">// Create a result table that depends on the three prior tables:</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">merged_tables </span><span style="color:#D73A49;--shiki-dark:#F97583">=</span><span style="color:#24292E;--shiki-dark:#E1E4E8"> merge(</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">    my_table_updated,</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">    my_table_filtered1,</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">    my_table_filtered2</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">)</span></span>
<span class="line"></span></code></pre>2f:["$","div",null,{"className":"codeblock-wrapper","children":[["$","$L35",null,{"code":"// Retrieve a live table:\nmy_table = get_my_kafka_feed_table()\n\n// Run several independent query operations on 'my_table':\nmy_table_updated = my_table.update(\"MyCalculation = computeValue(Col1, Col2, ColRed, ColBlue)\")\nmy_table_filtered1 = my_table.where(\"ColX < 10000\")\nmy_table_filtered2 = my_table.where(\"ColY > ColZ\")\n\n// Create a result table that depends on the three prior tables:\nmerged_tables = merge(\n    my_table_updated,\n    my_table_filtered1,\n    my_table_filtered2\n)\n"}],["$","div",null,{"className":"codeblock","data-lang":"groovy","dangerouslySetInnerHTML":{"__html":"$36"}}]]}]
37:T5c2,<pre class="shiki shiki-themes github-light github-dark" style="background-color:#fff;--shiki-dark-bg:#24292e;color:#24292e;--shiki-dark:#e1e4e8" tabindex="0"><code><span class="line"><span style="color:#D73A49;--shiki-dark:#F97583">import</span><span style="color:#24292E;--shiki-dark:#E1E4E8"> java.util.concurrent.atomic.AtomicInteger</span></span>
<span class="line"></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">a </span><span style="color:#D73A49;--shiki-dark:#F97583">=</span><span style="color:#D73A49;--shiki-dark:#F97583"> new</span><span style="color:#D73A49;--shiki-dark:#F97583"> AtomicInteger</span><span style="color:#24292E;--shiki-dark:#E1E4E8">(</span><span style="color:#005CC5;--shiki-dark:#79B8FF">0</span><span style="color:#24292E;--shiki-dark:#E1E4E8">)</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">t </span><span style="color:#D73A49;--shiki-dark:#F97583">=</span><span style="color:#24292E;--shiki-dark:#E1E4E8"> emptyTable(1_000_000)</span><span style="color:#D73A49;--shiki-dark:#F97583">.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">update(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"A=a.getAndIncrement()"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">, </span><span style="color:#032F62;--shiki-dark:#9ECBFF">"B=a.getAndIncrement()"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">)</span></span>
<span class="line"></span></code></pre>30:["$","div",null,{"className":"codeblock-wrapper","children":[["$","$L35",null,{"code":"import java.util.concurrent.atomic.AtomicInteger\n\na = new AtomicInteger(0)\nt = emptyTable(1_000_000).update(\"A=a.getAndIncrement()\", \"B=a.getAndIncrement()\")\n"}],["$","div",null,{"className":"codeblock","data-lang":"groovy","dangerouslySetInnerHTML":{"__html":"$37"}}]]}]
32:["$","div",null,{"className":"codeblock-wrapper","children":[["$","$L35",null,{"code":"t = emptyTable(1_000_000).update(\"A=i\", \"B=1_000_000 + i\")\n"}],["$","div",null,{"className":"codeblock","data-lang":"groovy","dangerouslySetInnerHTML":{"__html":"<pre class=\"shiki shiki-themes github-light github-dark\" style=\"background-color:#fff;--shiki-dark-bg:#24292e;color:#24292e;--shiki-dark:#e1e4e8\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">t </span><span style=\"color:#D73A49;--shiki-dark:#F97583\">=</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\"> emptyTable(1_000_000)</span><span style=\"color:#D73A49;--shiki-dark:#F97583\">.</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">update(</span><span style=\"color:#032F62;--shiki-dark:#9ECBFF\">\"A=i\"</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">, </span><span style=\"color:#032F62;--shiki-dark:#9ECBFF\">\"B=1_000_000 + i\"</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">)</span></span>\n<span class=\"line\"></span></code></pre>"}}]]}]
38:Tb6f,<pre class="shiki shiki-themes github-light github-dark" style="background-color:#fff;--shiki-dark-bg:#24292e;color:#24292e;--shiki-dark:#e1e4e8" tabindex="0"><code><span class="line"><span style="color:#D73A49;--shiki-dark:#F97583">import</span><span style="color:#24292E;--shiki-dark:#E1E4E8"> java.util.concurrent.atomic.AtomicInteger</span></span>
<span class="line"></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">a </span><span style="color:#D73A49;--shiki-dark:#F97583">=</span><span style="color:#D73A49;--shiki-dark:#F97583"> new</span><span style="color:#D73A49;--shiki-dark:#F97583"> AtomicInteger</span><span style="color:#24292E;--shiki-dark:#E1E4E8">(</span><span style="color:#005CC5;--shiki-dark:#79B8FF">0</span><span style="color:#24292E;--shiki-dark:#E1E4E8">)</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">t </span><span style="color:#D73A49;--shiki-dark:#F97583">=</span><span style="color:#24292E;--shiki-dark:#E1E4E8"> emptyTable(1_000_000)</span><span style="color:#D73A49;--shiki-dark:#F97583">.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">update(</span><span style="color:#D73A49;--shiki-dark:#F97583">List.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span></span>
<span class="line"><span style="color:#D73A49;--shiki-dark:#F97583">        Selectable.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#D73A49;--shiki-dark:#F97583">ColumnName.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"A"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">), </span><span style="color:#D73A49;--shiki-dark:#F97583">RawString.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"a.getAndIncrement()"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">))</span><span style="color:#D73A49;--shiki-dark:#F97583">.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">withDeclaredBarriers(a),</span></span>
<span class="line"><span style="color:#D73A49;--shiki-dark:#F97583">        Selectable.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#D73A49;--shiki-dark:#F97583">ColumnName.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"B"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">), </span><span style="color:#D73A49;--shiki-dark:#F97583">RawString.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"a.getAndIncrement()"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">))</span><span style="color:#D73A49;--shiki-dark:#F97583">.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">withRespectedBarriers(a)))</span></span>
<span class="line"></span></code></pre>33:["$","div",null,{"className":"codeblock-wrapper","children":[["$","$L35",null,{"code":"import java.util.concurrent.atomic.AtomicInteger\n\na = new AtomicInteger(0)\nt = emptyTable(1_000_000).update(List.of(\n        Selectable.of(ColumnName.of(\"A\"), RawString.of(\"a.getAndIncrement()\")).withDeclaredBarriers(a),\n        Selectable.of(ColumnName.of(\"B\"), RawString.of(\"a.getAndIncrement()\")).withRespectedBarriers(a)))\n"}],["$","div",null,{"className":"codeblock","data-lang":"groovy","dangerouslySetInnerHTML":{"__html":"$38"}}]]}]
39:Tad9,<pre class="shiki shiki-themes github-light github-dark" style="background-color:#fff;--shiki-dark-bg:#24292e;color:#24292e;--shiki-dark:#e1e4e8" tabindex="0"><code><span class="line"><span style="color:#D73A49;--shiki-dark:#F97583">import</span><span style="color:#24292E;--shiki-dark:#E1E4E8"> java.util.concurrent.atomic.AtomicInteger</span></span>
<span class="line"></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">a </span><span style="color:#D73A49;--shiki-dark:#F97583">=</span><span style="color:#D73A49;--shiki-dark:#F97583"> new</span><span style="color:#D73A49;--shiki-dark:#F97583"> AtomicInteger</span><span style="color:#24292E;--shiki-dark:#E1E4E8">(</span><span style="color:#005CC5;--shiki-dark:#79B8FF">0</span><span style="color:#24292E;--shiki-dark:#E1E4E8">)</span></span>
<span class="line"><span style="color:#24292E;--shiki-dark:#E1E4E8">t</span><span style="color:#D73A49;--shiki-dark:#F97583">=</span><span style="color:#24292E;--shiki-dark:#E1E4E8">emptyTable(1_000_000)</span><span style="color:#D73A49;--shiki-dark:#F97583">.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">update(</span><span style="color:#D73A49;--shiki-dark:#F97583">List.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span></span>
<span class="line"><span style="color:#D73A49;--shiki-dark:#F97583">        Selectable.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#D73A49;--shiki-dark:#F97583">ColumnName.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"A"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">), </span><span style="color:#D73A49;--shiki-dark:#F97583">RawString.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"a.getAndIncrement()"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">))</span><span style="color:#D73A49;--shiki-dark:#F97583">.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">withSerial(),</span></span>
<span class="line"><span style="color:#D73A49;--shiki-dark:#F97583">        Selectable.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#D73A49;--shiki-dark:#F97583">ColumnName.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"B"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">), </span><span style="color:#D73A49;--shiki-dark:#F97583">RawString.</span><span style="color:#24292E;--shiki-dark:#E1E4E8">of(</span><span style="color:#032F62;--shiki-dark:#9ECBFF">"a.getAndIncrement()"</span><span style="color:#24292E;--shiki-dark:#E1E4E8">))))</span></span>
<span class="line"></span></code></pre>34:["$","div",null,{"className":"codeblock-wrapper","children":[["$","$L35",null,{"code":"import java.util.concurrent.atomic.AtomicInteger\n\na = new AtomicInteger(0)\nt=emptyTable(1_000_000).update(List.of(\n        Selectable.of(ColumnName.of(\"A\"), RawString.of(\"a.getAndIncrement()\")).withSerial(),\n        Selectable.of(ColumnName.of(\"B\"), RawString.of(\"a.getAndIncrement()\"))))\n"}],["$","div",null,{"className":"codeblock","data-lang":"groovy","dangerouslySetInnerHTML":{"__html":"$39"}}]]}]