PostgreSQL怎么调用mergeruns函数

这篇文章主要介绍"PostgreSQL怎么调用mergeruns函数"，在日常操作中，相信很多人在PostgreSQL怎么调用mergeruns函数问题上存在疑惑，小编查阅了各式资料，整理出简单好用的操作方法，希望对大家解答"PostgreSQL怎么调用mergeruns函数"的疑惑有所帮助！接下来，请跟着小编一起来学习吧！

TupleTableSlot
执行器在"tuple table"中存储元组,这个表是各自独立的TupleTableSlots链表.

/*---------- * The executor stores tuples in a "tuple table" which is a List of * independent TupleTableSlots.  There are several cases we need to handle: *      1. physical tuple in a disk buffer page *      2. physical tuple constructed in palloc'ed memory *      3. "minimal" physical tuple constructed in palloc'ed memory *      4. "virtual" tuple consisting of Datum/isnull arrays * 执行器在"tuple table"中存储元组,这个表是各自独立的TupleTableSlots链表. * 有以下情况需要处理: *      1. 磁盘缓存页中的物理元组 *      2. 在已分配内存中构造的物理元组 *      3. 在已分配内存中构造的"minimal"物理元组 *      4. 含有Datum/isnull数组的"virtual"虚拟元组 * * The first two cases are similar in that they both deal with "materialized" * tuples, but resource management is different.  For a tuple in a disk page * we need to hold a pin on the buffer until the TupleTableSlot's reference * to the tuple is dropped; while for a palloc'd tuple we usually want the * tuple pfree'd when the TupleTableSlot's reference is dropped. * 最上面2种情况跟"物化"元组的处理方式类似,但资源管理是不同的. * 对于在磁盘页中的元组,需要pin在缓存中直至TupleTableSlot依赖的元组被清除, *   而对于通过palloc分配的元组在TupleTableSlot依赖被清除后通常希望使用pfree释放 * * A "minimal" tuple is handled similarly to a palloc'd regular tuple. * At present, minimal tuples never are stored in buffers, so there is no * parallel to case 1.  Note that a minimal tuple has no "system columns". * (Actually, it could have an OID, but we have no need to access the OID.) * "minimal"元组与通常的palloc分配的元组处理类似. * 截止目前为止,"minimal"元组不会存储在缓存中,因此对于第一种情况不会存在并行的问题. * 注意"minimal"没有"system columns"系统列 * (实际上,可以有OID,但不需要访问OID列) * * A "virtual" tuple is an optimization used to minimize physical data * copying in a nest of plan nodes.  Any pass-by-reference Datums in the * tuple point to storage that is not directly associated with the * TupleTableSlot; generally they will point to part of a tuple stored in * a lower plan node's output TupleTableSlot, or to a function result * constructed in a plan node's per-tuple econtext.  It is the responsibility * of the generating plan node to be sure these resources are not released * for as long as the virtual tuple needs to be valid.  We only use virtual * tuples in the result slots of plan nodes --- tuples to be copied anywhere * else need to be "materialized" into physical tuples.  Note also that a * virtual tuple does not have any "system columns". * "virtual"元组是用于在嵌套计划节点中拷贝时最小化物理数据的优化. * 所有通过引用传递指向与TupleTableSlot非直接相关的存储的元组的Datums使用, *   通常它们会指向存储在低层节点输出的TupleTableSlot中的元组的一部分, *   或者指向在计划节点的per-tuple内存上下文econtext中构造的函数结果. * 产生计划节点的时候有责任确保这些资源未被释放,确保virtual元组是有效的. * 我们使用计划节点中的结果slots中的虚拟元组 --- 元组会拷贝到其他地方需要"物化"到物理元组中. * 注意virtual元组不需要有"system columns" * * It is also possible for a TupleTableSlot to hold both physical and minimal * copies of a tuple.  This is done when the slot is requested to provide * the format other than the one it currently holds.  (Originally we attempted * to handle such requests by replacing one format with the other, but that * had the fatal defect of invalidating any pass-by-reference Datums pointing * into the existing slot contents.)  Both copies must contain identical data * payloads when this is the case. * TupleTableSlot包含物理和minimal元组拷贝是可能的. * 在slot需要提供格式化而不是当前持有的格式时会出现这种情况. * (原始的情况是我们准备通过另外一种格式进行替换来处理这种请求,但在校验引用传递Datums时会出现致命错误) * 同时在这种情况下,拷贝必须含有唯一的数据payloads. * * The Datum/isnull arrays of a TupleTableSlot serve double duty.  When the * slot contains a virtual tuple, they are the authoritative data.  When the * slot contains a physical tuple, the arrays contain data extracted from * the tuple.  (In this state, any pass-by-reference Datums point into * the physical tuple.)  The extracted information is built "lazily", * ie, only as needed.  This serves to avoid repeated extraction of data * from the physical tuple. * TupleTableSlot中的Datum/isnull数组有双重职责. * 在slot包含虚拟元组时,它们是authoritative(权威)数据. * 在slot包含物理元组时,时包含从元组中提取的数据的数组. * (在这种情况下,所有通过引用传递的Datums指向物理元组) * 提取的信息通过'lazily'在需要的时候才构建. * 这样可以避免从物理元组的重复数据提取. * * A TupleTableSlot can also be "empty", holding no valid data.  This is * the only valid state for a freshly-created slot that has not yet had a * tuple descriptor assigned to it.  In this state, tts_isempty must be * true, tts_shouldFree false, tts_tuple NULL, tts_buffer InvalidBuffer, * and tts_nvalid zero. * TupleTableSlot可能为"empty",没有有效数据. * 对于新鲜创建仍未分配描述的的slot来说这是唯一有效的状态. * 在这种状态下,tts_isempty必须为T,tts_shouldFree为F, tts_tuple为NULL, *   tts_buffer为InvalidBuffer,tts_nvalid为0. * * The tupleDescriptor is simply referenced, not copied, by the TupleTableSlot * code.  The caller of ExecSetSlotDescriptor() is responsible for providing * a descriptor that will live as long as the slot does.  (Typically, both * slots and descriptors are in per-query memory and are freed by memory * context deallocation at query end; so it's not worth providing any extra * mechanism to do more.  However, the slot will increment the tupdesc * reference count if a reference-counted tupdesc is supplied.) * tupleDescriptor只是简单的引用并没有通过TupleTableSlot中的代码进行拷贝. * ExecSetSlotDescriptor()的调用者有责任提供与slot生命周期一样的描述符. * (典型的,不管是slots还是描述符会在per-query内存中, *  并且会在查询结束时通过内存上下文的析构器释放,因此不需要提供额外的机制来处理. *  但是,如果使用了引用计数型tupdesc,slot会增加tupdesc引用计数) * * When tts_shouldFree is true, the physical tuple is "owned" by the slot * and should be freed when the slot's reference to the tuple is dropped. * 在tts_shouldFree为T的情况下,物理元组由slot持有,并且在slot引用元组被清除时释放内存. * * If tts_buffer is not InvalidBuffer, then the slot is holding a pin * on the indicated buffer page; drop the pin when we release the * slot's reference to that buffer.  (tts_shouldFree should always be * false in such a case, since presumably tts_tuple is pointing at the * buffer page.) * 如tts_buffer不是InvalidBuffer,那么slot持有缓存页中的pin,在释放引用该buffer的slot时会清除该pin. * (tts_shouldFree通常来说应为F,因为tts_tuple会指向缓存页) * * tts_nvalid indicates the number of valid columns in the tts_values/isnull * arrays.  When the slot is holding a "virtual" tuple this must be equal * to the descriptor's natts.  When the slot is holding a physical tuple * this is equal to the number of columns we have extracted (we always * extract columns from left to right, so there are no holes). * tts_nvalid指示了tts_values/isnull数组中的有效列数. * 如果slot含有虚拟元组,该字段必须跟描述符的natts一样. * 在slot含有物理元组时,该字段等于我们提取的列数. * (我们通常从左到右提取列,因此不会有空洞存在) * * tts_values/tts_isnull are allocated when a descriptor is assigned to the * slot; they are of length equal to the descriptor's natts. * 在描述符分配给slot时tts_values/tts_isnull会被分配内存,长度与描述符natts长度一样. * * tts_mintuple must always be NULL if the slot does not hold a "minimal" * tuple.  When it does, tts_mintuple points to the actual MinimalTupleData * object (the thing to be pfree'd if tts_shouldFreeMin is true).  If the slot * has only a minimal and not also a regular physical tuple, then tts_tuple * points at tts_minhdr and the fields of that struct are set correctly * for access to the minimal tuple; in particular, tts_minhdr.t_data points * MINIMAL_TUPLE_OFFSET bytes before tts_mintuple.  This allows column * extraction to treat the case identically to regular physical tuples. * 如果slot没有包含minimal元组,tts_mintuple通常必须为NULL. * 如含有,则tts_mintuple执行实际的MinimalTupleData对象(如tts_shouldFreeMin为T,则需要通过pfree释放内存). * 如果slot只有一个minimal而没有通常的物理元组,那么tts_tuple指向tts_minhdr, *   结构体的其他字段会被正确的设置为用于访问minimal元组. *   特别的, tts_minhdr.t_data指向tts_mintuple前的MINIMAL_TUPLE_OFFSET字节. * 这可以让列提取可以独立处理通常的物理元组. * * tts_slow/tts_off are saved state for slot_deform_tuple, and should not * be touched by any other code. * tts_slow/tts_off用于存储slot_deform_tuple状态,不应通过其他代码修改. *---------- */typedef struct TupleTableSlot{    NodeTag     type;//Node标记    //如slot为空,则为T    bool        tts_isempty;    /* true = slot is empty */    //是否需要pfree tts_tuple?    bool        tts_shouldFree; /* should pfree tts_tuple? */    //是否需要pfree tts_mintuple?    bool        tts_shouldFreeMin;  /* should pfree tts_mintuple? */#define FIELDNO_TUPLETABLESLOT_SLOW 4    //为slot_deform_tuple存储状态?    bool        tts_slow;       /* saved state for slot_deform_tuple */#define FIELDNO_TUPLETABLESLOT_TUPLE 5    //物理元组,如为虚拟元组则为NULL    HeapTuple   tts_tuple;      /* physical tuple, or NULL if virtual */#define FIELDNO_TUPLETABLESLOT_TUPLEDESCRIPTOR 6    //slot中的元组描述符    TupleDesc   tts_tupleDescriptor;    /* slot's tuple descriptor */    //slot所在的上下文    MemoryContext tts_mcxt;     /* slot itself is in this context */    //元组缓存,如无则为InvalidBuffer    Buffer      tts_buffer;     /* tuple's buffer, or InvalidBuffer */#define FIELDNO_TUPLETABLESLOT_NVALID 9    //tts_values中的有效值    int         tts_nvalid;     /* # of valid values in tts_values */#define FIELDNO_TUPLETABLESLOT_VALUES 10    //当前每个属性的值    Datum      *tts_values;     /* current per-attribute values */#define FIELDNO_TUPLETABLESLOT_ISNULL 11    //isnull数组    bool       *tts_isnull;     /* current per-attribute isnull flags */    //minimal元组,如无则为NULL    MinimalTuple tts_mintuple;  /* minimal tuple, or NULL if none */    //在minimal情况下的工作空间    HeapTupleData tts_minhdr;   /* workspace for minimal-tuple-only case */#define FIELDNO_TUPLETABLESLOT_OFF 14    //slot_deform_tuple的存储状态    uint32      tts_off;        /* saved state for slot_deform_tuple */    //不能被变更的描述符(固定描述符)    bool        tts_fixedTupleDescriptor;   /* descriptor can't be changed */} TupleTableSlot;/* base tuple table slot type */typedef struct TupleTableSlot{    NodeTag     type;//Node标记#define FIELDNO_TUPLETABLESLOT_FLAGS 1    uint16      tts_flags;      /* 布尔状态;Boolean states */#define FIELDNO_TUPLETABLESLOT_NVALID 2    AttrNumber  tts_nvalid;     /* 在tts_values中有多少有效的values;# of valid values in tts_values */    const TupleTableSlotOps *const tts_ops; /* slot的实际实现;implementation of slot */#define FIELDNO_TUPLETABLESLOT_TUPLEDESCRIPTOR 4    TupleDesc   tts_tupleDescriptor;    /* slot的元组描述符;slot's tuple descriptor */#define FIELDNO_TUPLETABLESLOT_VALUES 5    Datum      *tts_values;     /* 当前属性值;current per-attribute values */#define FIELDNO_TUPLETABLESLOT_ISNULL 6    bool       *tts_isnull;     /* 当前属性isnull标记;current per-attribute isnull flags */    MemoryContext tts_mcxt;     /*内存上下文; slot itself is in this context */} TupleTableSlot;/* routines for a TupleTableSlot implementation *///TupleTableSlot的"小程序"struct TupleTableSlotOps{    /* Minimum size of the slot */    //slot的最小化大小    size_t          base_slot_size;    /* Initialization. */    //初始化方法    void (*init)(TupleTableSlot *slot);    /* Destruction. */    //析构方法    void (*release)(TupleTableSlot *slot);    /*     * Clear the contents of the slot. Only the contents are expected to be     * cleared and not the tuple descriptor. Typically an implementation of     * this callback should free the memory allocated for the tuple contained     * in the slot.     * 清除slot中的内容。     * 只希望清除内容，而不希望清除元组描述符。     * 通常，这个回调的实现应该释放为slot中包含的元组分配的内存。     */    void (*clear)(TupleTableSlot *slot);    /*     * Fill up first natts entries of tts_values and tts_isnull arrays with     * values from the tuple contained in the slot. The function may be called     * with natts more than the number of attributes available in the tuple,     * in which case it should set tts_nvalid to the number of returned     * columns.     * 用slot中包含的元组的值填充tts_values和tts_isnull数组的第一个natts条目。     * 在调用该函数时，natts可能多于元组中可用属性的数量，在这种情况下，     *   应该将tts_nvalid设置为返回列的数量。     */    void (*getsomeattrs)(TupleTableSlot *slot, int natts);    /*     * Returns value of the given system attribute as a datum and sets isnull     * to false, if it's not NULL. Throws an error if the slot type does not     * support system attributes.     * 将给定系统属性的值作为基准返回，如果不为NULL，     *   则将isnull设置为false。如果slot类型不支持系统属性，则引发错误。     */    Datum (*getsysattr)(TupleTableSlot *slot, int attnum, bool *isnull);    /*     * Make the contents of the slot solely depend on the slot, and not on     * underlying resources (like another memory context, buffers, etc).     * 使slot的内容完全依赖于slot，而不是底层资源(如另一个内存上下文、缓冲区等)。     */    void (*materialize)(TupleTableSlot *slot);    /*     * Copy the contents of the source slot into the destination slot's own     * context. Invoked using callback of the destination slot.     * 将源slot的内容复制到目标slot自己的上下文中。     * 使用目标slot的回调函数调用。     */    void (*copyslot) (TupleTableSlot *dstslot, TupleTableSlot *srcslot);    /*     * Return a heap tuple "owned" by the slot. It is slot's responsibility to     * free the memory consumed by the heap tuple. If the slot can not "own" a     * heap tuple, it should not implement this callback and should set it as     * NULL.     * 返回slot"拥有"的堆元组。     * slot负责释放堆元组分配的内存。     * 如果slot不能"拥有"堆元组，它不应该实现这个回调函数，应该将它设置为NULL。     */    HeapTuple (*get_heap_tuple)(TupleTableSlot *slot);    /*     * Return a minimal tuple "owned" by the slot. It is slot's responsibility     * to free the memory consumed by the minimal tuple. If the slot can not     * "own" a minimal tuple, it should not implement this callback and should     * set it as NULL.     * 返回slot"拥有"的最小元组。     * slot负责释放最小元组分配的内存。     * 如果slot不能"拥有"最小元组，它不应该实现这个回调函数，应该将它设置为NULL。     */    MinimalTuple (*get_minimal_tuple)(TupleTableSlot *slot);    /*     * Return a copy of heap tuple representing the contents of the slot. The     * copy needs to be palloc'd in the current memory context. The slot     * itself is expected to remain unaffected. It is *not* expected to have     * meaningful "system columns" in the copy. The copy is not be "owned" by     * the slot i.e. the caller has to take responsibilty to free memory     * consumed by the slot.     * 返回表示slot内容的堆元组副本。     * 需要在当前内存上下文中对副本进行内存分配palloc。     * 预计slot本身不会受到影响。     * 它不希望在副本中有有意义的"系统列"。副本不是slot"拥有"的，即调用方必须负责释放slot消耗的内存。     */    HeapTuple (*copy_heap_tuple)(TupleTableSlot *slot);    /*     * Return a copy of minimal tuple representing the contents of the slot. The     * copy needs to be palloc'd in the current memory context. The slot     * itself is expected to remain unaffected. It is *not* expected to have     * meaningful "system columns" in the copy. The copy is not be "owned" by     * the slot i.e. the caller has to take responsibilty to free memory     * consumed by the slot.     * 返回表示slot内容的最小元组的副本。     * 需要在当前内存上下文中对副本进行palloc。     * 预计slot本身不会受到影响。     * 它不希望在副本中有有意义的"系统列"。副本不是slot"拥有"的，即调用方必须负责释放slot消耗的内存。     */    MinimalTuple (*copy_minimal_tuple)(TupleTableSlot *slot);};typedef struct tupleDesc{    int         natts;          /* tuple中的属性数量;number of attributes in the tuple */    Oid         tdtypeid;       /* tuple类型的组合类型ID;composite type ID for tuple type */    int32       tdtypmod;       /* tuple类型的typmode;typmod for tuple type */    int         tdrefcount;     /* 依赖计数,如为-1,则没有依赖;reference count, or -1 if not counting */    TupleConstr *constr;        /* 约束,如无则为NULL;constraints, or NULL if none */    /* attrs[N] is the description of Attribute Number N+1 */    //attrs[N]是第N+1个属性的描述符    FormData_pg_attribute attrs[FLEXIBLE_ARRAY_MEMBER];}  *TupleDesc;

SortState
排序运行期状态信息

/* ---------------- *   SortState information *   排序运行期状态信息 * ---------------- */typedef struct SortState{    //基类    ScanState   ss;             /* its first field is NodeTag */    //是否需要随机访问排序输出?    bool        randomAccess;   /* need random access to sort output? */    //结果集是否存在边界?    bool        bounded;        /* is the result set bounded? */    //如存在边界,需要多少个元组?    int64       bound;          /* if bounded, how many tuples are needed */    //是否已完成排序?    bool        sort_Done;      /* sort completed yet? */    //是否使用有界值?    bool        bounded_Done;   /* value of bounded we did the sort with */    //使用的有界值?    int64       bound_Done;     /* value of bound we did the sort with */    //tuplesort.c的私有状态    void       *tuplesortstate; /* private state of tuplesort.c */    //是否worker?    bool        am_worker;      /* are we a worker? */    //每个worker对应一个条目    SharedSortInfo *shared_info;    /* one entry per worker */} SortState;/* ---------------- *   Shared memory container for per-worker sort information *   per-worker排序信息的共享内存容器 * ---------------- */typedef struct SharedSortInfo{    //worker个数?    int         num_workers;    //排序机制    TuplesortInstrumentation sinstrument[FLEXIBLE_ARRAY_MEMBER];} SharedSortInfo;

TuplesortInstrumentation
报告排序统计的数据结构.

/* * Data structures for reporting sort statistics.  Note that * TuplesortInstrumentation can't contain any pointers because we * sometimes put it in shared memory. * 报告排序统计的数据结构. * 注意TuplesortInstrumentation不能包含指针因为有时候会把该结构体放在共享内存中. */typedef enum{    SORT_TYPE_STILL_IN_PROGRESS = 0,//仍然在排序中    SORT_TYPE_TOP_N_HEAPSORT,//TOP N 堆排序    SORT_TYPE_QUICKSORT,//快速排序    SORT_TYPE_EXTERNAL_SORT,//外排序    SORT_TYPE_EXTERNAL_MERGE//外排序后的合并} TuplesortMethod;//排序方法typedef enum{    SORT_SPACE_TYPE_DISK,//需要用上磁盘    SORT_SPACE_TYPE_MEMORY//使用内存} TuplesortSpaceType;typedef struct TuplesortInstrumentation{    //使用的排序算法    TuplesortMethod sortMethod; /* sort algorithm used */    //排序使用空间类型    TuplesortSpaceType spaceType;   /* type of space spaceUsed represents */    //空间消耗(以K为单位)    long        spaceUsed;      /* space consumption, in kB */} TuplesortInstrumentation;

二、源码解读

mergeruns归并所有已完成初始轮的数据.

/* * mergeruns -- merge all the completed initial runs. * mergeruns -- 归并所有已完成的数据. * * This implements steps D5, D6 of Algorithm D.  All input data has * already been written to initial runs on tape (see dumptuples). * 实现了算法D中的D5和D6. * 所有输入数据已写入到磁盘上(dumptuples函数负责完成). */static voidmergeruns(Tuplesortstate *state){    int         tapenum,                svTape,                svRuns,                svDummy;    int         numTapes;    int         numInputTapes;    Assert(state->status == TSS_BUILDRUNS);    Assert(state->memtupcount == 0);    if (state->sortKeys != NULL && state->sortKeys->abbrev_converter != NULL)    {        /*         * If there are multiple runs to be merged, when we go to read back         * tuples from disk, abbreviated keys will not have been stored, and         * we don't care to regenerate them.  Disable abbreviation from this         * point on.         * 如果从磁盘上读回元组时存在多个运行需要被归并,         *   缩写键不会被存储,并不关系是否需要重新生成它们.         * 在这一刻起,禁用缩写.         */        state->sortKeys->abbrev_converter = NULL;        state->sortKeys->comparator = state->sortKeys->abbrev_full_comparator;        /* Not strictly necessary, but be tidy */        //非严格性需要,但需要tidy        state->sortKeys->abbrev_abort = NULL;        state->sortKeys->abbrev_full_comparator = NULL;    }    /*     * Reset tuple memory.  We've freed all the tuples that we previously     * allocated.  We will use the slab allocator from now on.     * 重置元组内存.     * 已释放了先前分配的内存.从现在起使用slab分配器.     */    MemoryContextDelete(state->tuplecontext);    state->tuplecontext = NULL;    /*     * We no longer need a large memtuples array.  (We will allocate a smaller     * one for the heap later.)     * 不再需要大块的memtuples数组.(将为后面的堆分配更小块的内存)     */    FREEMEM(state, GetMemoryChunkSpace(state->memtuples));    pfree(state->memtuples);    state->memtuples = NULL;    /*     * If we had fewer runs than tapes, refund the memory that we imagined we     * would need for the tape buffers of the unused tapes.     * 比起tapes,如果runs要少, 退还我们认为需要用于tape缓存但其实用不上的内存.     *     * numTapes and numInputTapes reflect the actual number of tapes we will     * use.  Note that the output tape's tape number is maxTapes - 1, so the     * tape numbers of the used tapes are not consecutive, and you cannot just     * loop from 0 to numTapes to visit all used tapes!     * numTapes和numInputTapes反映了实际的使用tapes数.     * 注意输出的tape编号是maxTapes - 1,因此已使用的tape编号不是连续的,     *   不能简单的从0 - numTapes循环访问所有已使用的tapes.     */    if (state->Level == 1)    {        numInputTapes = state->currentRun;        numTapes = numInputTapes + 1;        FREEMEM(state, (state->maxTapes - numTapes) * TAPE_BUFFER_OVERHEAD);    }    else    {        numInputTapes = state->tapeRange;        numTapes = state->maxTapes;    }    /*     * Initialize the slab allocator.  We need one slab slot per input tape,     * for the tuples in the heap, plus one to hold the tuple last returned     * from tuplesort_gettuple.  (If we're sorting pass-by-val Datums,     * however, we don't need to do allocate anything.)     * 初始化slab分配器.每一个输入的tape都有一个slab slot,对于堆中的元组,     *   外加1用于保存最后从tuplesort_gettuple返回的元组.     * (但是,如果通过传值的方式传递Datums,不需要执行内存分配)     *     * From this point on, we no longer use the USEMEM()/LACKMEM() mechanism     * to track memory usage of individual tuples.     * 从这点起,不再使用USEMEM()/LACKMEM()这种机制来跟踪独立元组的内存使用.     */    if (state->tuples)        init_slab_allocator(state, numInputTapes + 1);    else        init_slab_allocator(state, 0);    /*     * Allocate a new 'memtuples' array, for the heap.  It will hold one tuple     * from each input tape.     * 为堆分配新的'memtuples'数组     * 对于每一个输入的tape,都会保存有一个元组.     */    state->memtupsize = numInputTapes;    state->memtuples = (SortTuple *) palloc(numInputTapes * sizeof(SortTuple));    USEMEM(state, GetMemoryChunkSpace(state->memtuples));    /*     * Use all the remaining memory we have available for read buffers among     * the input tapes.     * 使用所有可使用的剩余内存读取输入tapes之间的缓存.     *     * We don't try to "rebalance" the memory among tapes, when we start a new     * merge phase, even if some tapes are inactive in the new phase.  That     * would be hard, because logtape.c doesn't know where one run ends and     * another begins.  When a new merge phase begins, and a tape doesn't     * participate in it, its buffer nevertheless already contains tuples from     * the next run on same tape, so we cannot release the buffer.  That's OK     * in practice, merge performance isn't that sensitive to the amount of     * buffers used, and most merge phases use all or almost all tapes,     * anyway.     * 在新的阶段就算存在某些tapes不再活动,在开始新的归并阶段时,不再尝试在tapes之间重平衡内存.     * 这是比较难以实现的,因为logtape.c不知道某个运行在哪里结束了,那个运行在哪里开始.     * 在新的归并阶段开始时,tape不需要分享,尽管如此,它的缓冲区已包含来自同一tape上下一次运行需要的元组,     * 因此不需要释放缓冲区.     * 实践中,这是没有问题的,归并的性能对于缓存的使用不是性能敏感的,大多数归并阶段使用所有或大多数的tapes.     */#ifdef TRACE_SORT    if (trace_sort)        elog(LOG, "worker %d using " INT64_FORMAT " KB of memory for read buffers among %d input tapes",             state->worker, state->availMem / 1024, numInputTapes);#endif    state->read_buffer_size = Max(state->availMem / numInputTapes, 0);    USEMEM(state, state->read_buffer_size * numInputTapes);    /* End of step D2: rewind all output tapes to prepare for merging */    //D2完成,倒回所有输出tapes准备归并    for (tapenum = 0; tapenum < state->tapeRange; tapenum++)        LogicalTapeRewindForRead(state->tapeset, tapenum, state->read_buffer_size);    for (;;)    {        //------------- 循环        /*         * At this point we know that tape[T] is empty.  If there's just one         * (real or dummy) run left on each input tape, then only one merge         * pass remains.  If we don't have to produce a materialized sorted         * tape, we can stop at this point and do the final merge on-the-fly.         * 在这时候,我们已知tape[T]是空的.         * 如果正好在每一个输入tape上只剩下某个run(实际或者虚拟的),那么只剩下一次归并.         * 如果不需要产生物化排序后的tape,这时候可以停止并执行内存中的最终归并.         */        if (!state->randomAccess && !WORKER(state))        {            bool        allOneRun = true;            Assert(state->tp_runs[state->tapeRange] == 0);            for (tapenum = 0; tapenum < state->tapeRange; tapenum++)            {                if (state->tp_runs[tapenum] + state->tp_dummy[tapenum] != 1)                {                    allOneRun = false;                    break;                }            }            if (allOneRun)            {                /* Tell logtape.c we won't be writing anymore */                //通知logtape.c,不再写入.                LogicalTapeSetForgetFreeSpace(state->tapeset);                /* Initialize for the final merge pass */                //为最终的归并做准备                beginmerge(state);                state->status = TSS_FINALMERGE;                return;            }        }        /* Step D5: merge runs onto tape[T] until tape[P] is empty */        //步骤D5:归并runs到tape[T]中直至tape[P]为空        while (state->tp_runs[state->tapeRange - 1] ||               state->tp_dummy[state->tapeRange - 1])        {            bool        allDummy = true;            for (tapenum = 0; tapenum < state->tapeRange; tapenum++)            {                if (state->tp_dummy[tapenum] == 0)                {                    allDummy = false;                    break;                }            }            if (allDummy)            {                state->tp_dummy[state->tapeRange]++;                for (tapenum = 0; tapenum < state->tapeRange; tapenum++)                    state->tp_dummy[tapenum]--;            }            else                mergeonerun(state);        }        /* Step D6: decrease level */        //步骤D6:往上层汇总        if (--state->Level == 0)            break;        /* rewind output tape T to use as new input */        //倒回输入的Tape T作为新的输入        LogicalTapeRewindForRead(state->tapeset, state->tp_tapenum[state->tapeRange],                                 state->read_buffer_size);        /* rewind used-up input tape P, and prepare it for write pass */        //倒回使用上的输入tape P,并为写入轮准备        LogicalTapeRewindForWrite(state->tapeset, state->tp_tapenum[state->tapeRange - 1]);        state->tp_runs[state->tapeRange - 1] = 0;        /*         * reassign tape units per step D6; note we no longer care about A[]         * 每一个步骤D6,重分配tape单元.         * 注意我们不再关心A[]了.         */        svTape = state->tp_tapenum[state->tapeRange];        svDummy = state->tp_dummy[state->tapeRange];        svRuns = state->tp_runs[state->tapeRange];        for (tapenum = state->tapeRange; tapenum > 0; tapenum--)        {            state->tp_tapenum[tapenum] = state->tp_tapenum[tapenum - 1];            state->tp_dummy[tapenum] = state->tp_dummy[tapenum - 1];            state->tp_runs[tapenum] = state->tp_runs[tapenum - 1];        }        state->tp_tapenum[0] = svTape;        state->tp_dummy[0] = svDummy;        state->tp_runs[0] = svRuns;    }    /*     * Done.  Knuth says that the result is on TAPE[1], but since we exited     * the loop without performing the last iteration of step D6, we have not     * rearranged the tape unit assignment, and therefore the result is on     * TAPE[T].  We need to do it this way so that we can freeze the final     * output tape while rewinding it.  The last iteration of step D6 would be     * a waste of cycles anyway...     * 大功告成!结果位于TAPE[1]中,但因为没有执行步骤D6中最后一个迭代就退出了循环,     *   因此不需要重新整理tape单元分配,因此结果在TAPE[T]中.     * 通过这种方法来处理一遍可以在倒回时冻结结果输出TAPE.     * 步骤D6的最后一轮迭代会是浪费.     */    state->result_tape = state->tp_tapenum[state->tapeRange];    if (!WORKER(state))        LogicalTapeFreeze(state->tapeset, state->result_tape, NULL);    else        worker_freeze_result_tape(state);    state->status = TSS_SORTEDONTAPE;    /* Release the read buffers of all the other tapes, by rewinding them. */    //通过倒回tapes,释放所有其他tapes的读缓存    for (tapenum = 0; tapenum < state->maxTapes; tapenum++)    {        if (tapenum != state->result_tape)            LogicalTapeRewindForWrite(state->tapeset, tapenum);    }}

三、跟踪分析

测试脚本

select * from t_sort order by c1,c2;

跟踪分析

(gdb) b mergerunsBreakpoint 1 at 0xa73508: file tuplesort.c, line 2570.(gdb) Note: breakpoint 1 also set at pc 0xa73508.Breakpoint 2 at 0xa73508: file tuplesort.c, line 2570.

输入参数

(gdb) cContinuing.Breakpoint 1, mergeruns (state=0x2b808a8) at tuplesort.c:25702570        Assert(state->status == TSS_BUILDRUNS);(gdb) p *state$1 = {status = TSS_BUILDRUNS, nKeys = 2, randomAccess = false, bounded = false, boundUsed = false, bound = 0,   tuples = true, availMem = 3164456, allowedMem = 4194304, maxTapes = 16, tapeRange = 15, sortcontext = 0x2b80790,   tuplecontext = 0x2b827a0, tapeset = 0x2b81480, comparetup = 0xa7525b ,   copytup = 0xa76247 , writetup = 0xa76de1 , readtup = 0xa76ec6 ,   memtuples = 0x7f0cfeb14050, memtupcount = 0, memtupsize = 37448, growmemtuples = false, slabAllocatorUsed = false,   slabMemoryBegin = 0x0, slabMemoryEnd = 0x0, slabFreeHead = 0x0, read_buffer_size = 0, lastReturnedTuple = 0x0,   currentRun = 3, mergeactive = 0x2b81350, Level = 1, destTape = 2, tp_fib = 0x2b80d58, tp_runs = 0x2b81378,   tp_dummy = 0x2b813d0, tp_tapenum = 0x2b81428, activeTapes = 0, result_tape = -1, current = 0, eof_reached = false,   markpos_block = 0, markpos_offset = 0, markpos_eof = false, worker = -1, shared = 0x0, nParticipants = -1,   tupDesc = 0x2b67ae0, sortKeys = 0x2b80cc0, onlyKey = 0x0, abbrevNext = 10, indexInfo = 0x0, estate = 0x0, heapRel = 0x0,   indexRel = 0x0, enforceUnique = false, high_mask = 0, low_mask = 0, max_buckets = 0, datumType = 0, datumTypeLen = 0,   ru_start = {tv = {tv_sec = 0, tv_usec = 0}, ru = {ru_utime = {tv_sec = 0, tv_usec = 0}, ru_stime = {tv_sec = 0,         tv_usec = 0}, {ru_maxrss = 0, __ru_maxrss_word = 0}, {ru_ixrss = 0, __ru_ixrss_word = 0}, {ru_idrss = 0,         __ru_idrss_word = 0}, {ru_isrss = 0, __ru_isrss_word = 0}, {ru_minflt = 0, __ru_minflt_word = 0}, {ru_majflt = 0,         __ru_majflt_word = 0}, {ru_nswap = 0, __ru_nswap_word = 0}, {ru_inblock = 0, __ru_inblock_word = 0}, {        ru_oublock = 0, __ru_oublock_word = 0}, {ru_msgsnd = 0, __ru_msgsnd_word = 0}, {ru_msgrcv = 0,         __ru_msgrcv_word = 0}, {ru_nsignals = 0, __ru_nsignals_word = 0}, {ru_nvcsw = 0, __ru_nvcsw_word = 0}, {        ru_nivcsw = 0, __ru_nivcsw_word = 0}}}}(gdb)

排序键等信息

(gdb) n2571        Assert(state->memtupcount == 0);(gdb) 2573        if (state->sortKeys != NULL && state->sortKeys->abbrev_converter != NULL)(gdb) p *state->sortKeys$2 = {ssup_cxt = 0x2b80790, ssup_collation = 0, ssup_reverse = false, ssup_nulls_first = false, ssup_attno = 2,   ssup_extra = 0x0, comparator = 0x4fd4af , abbreviate = true, abbrev_converter = 0x0, abbrev_abort = 0x0,   abbrev_full_comparator = 0x0}(gdb) p *state->sortKeys->abbrev_converterCannot access memory at address 0x0

重置元组内存,不再需要大块的memtuples数组.

(gdb) n2593        MemoryContextDelete(state->tuplecontext);(gdb) 2594        state->tuplecontext = NULL;(gdb) (gdb) n2600        FREEMEM(state, GetMemoryChunkSpace(state->memtuples));(gdb) 2601        pfree(state->memtuples);(gdb) 2602        state->memtuples = NULL;(gdb) 2613        if (state->Level == 1)(gdb)

计算Tapes数

(gdb) n2615            numInputTapes = state->currentRun;(gdb) p state->currentRun$3 = 3(gdb) p state->Level$4 = 1(gdb) p state->tapeRange$5 = 15(gdb) p state->maxTapes$6 = 16(gdb) n2616            numTapes = numInputTapes + 1;(gdb) 2617            FREEMEM(state, (state->maxTapes - numTapes) * TAPE_BUFFER_OVERHEAD);(gdb) 2634        if (state->tuples)(gdb) p numInputTapes$7 = 3(gdb) p numTapes$8 = 4(gdb)

初始化slab分配器/为堆分配新的'memtuples'数组/倒回所有输出tapes准备归并

(gdb) n2635            init_slab_allocator(state, numInputTapes + 1);(gdb) n2643        state->memtupsize = numInputTapes;(gdb) 2644        state->memtuples = (SortTuple *) palloc(numInputTapes * sizeof(SortTuple));(gdb) 2645        USEMEM(state, GetMemoryChunkSpace(state->memtuples));(gdb) p state->memtupsize$9 = 3(gdb) n2662        if (trace_sort)(gdb) 2667        state->read_buffer_size = Max(state->availMem / numInputTapes, 0);(gdb) 2668        USEMEM(state, state->read_buffer_size * numInputTapes);(gdb) p state->read_buffer_size$10 = 1385762(gdb) n2671        for (tapenum = 0; tapenum < state->tapeRange; tapenum++)(gdb) 2672            LogicalTapeRewindForRead(state->tapeset, tapenum, state->read_buffer_size);(gdb) p state->tapeRange$11 = 15(gdb) p state->status$12 = TSS_BUILDRUNS(gdb)

进入循环

2671        for (tapenum = 0; tapenum < state->tapeRange; tapenum++)(gdb) 2682            if (!state->randomAccess && !WORKER(state))(gdb) 2684                bool        allOneRun = true;(gdb) p state->randomAccess$15 = false(gdb) p WORKER(state)$16 = 0(gdb)

循环判断allOneRun是否为F

2687                for (tapenum = 0; tapenum < state->tapeRange; tapenum++)(gdb) 2695                if (allOneRun)(gdb) p allOneRun$19 = true(gdb)

开始归并,并设置状态,返回

(gdb) n2698                    LogicalTapeSetForgetFreeSpace(state->tapeset);(gdb) 2700                    beginmerge(state);(gdb) 2701                    state->status = TSS_FINALMERGE;(gdb) 2702                    return;(gdb) 2779    }(gdb) tuplesort_performsort (state=0x2b808a8) at tuplesort.c:18661866                state->eof_reached = false;(gdb)

完成排序

(gdb) n1867                state->markpos_block = 0L;(gdb) 1868                state->markpos_offset = 0;(gdb) 1869                state->markpos_eof = false;(gdb) 1870                break;(gdb) 1878        if (trace_sort)(gdb) 1890        MemoryContextSwitchTo(oldcontext);(gdb) 1891    }(gdb) ExecSort (pstate=0x2b67640) at nodeSort.c:123123         estate->es_direction = dir;(gdb) cContinuing.

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